Link adaptation for IEEE 802.11a WLAN over fading …kom.aau.dk/~hcn/publications/semester9.report.pdf1.1.1 Advantages and disadvantages of WLAN TheWLANtechnologiesaresosuccessfulbecauseito

Link adaptation for IEEE 802.11a WLAN over fadingchannel

Department of Communication Technology January 2nd, 2004Aalborg University

Mobile Communications Group 992, the 9th Semester

AALBORG UNIVERSITYINSTITUTE OF ELECTRONIC SYSTEMSDEPARTMENT OF COMMUNICATION TECHNOLOGY

Fredrik Bajersvej 7 DK-9220 Aalborg East Phone 96 35 80 80Title: Link adaptation for IEEE 802.11a WLAN over fading channelProject period: The 9th Semester, September 2003 to January 2004Project group: Mobile Communcations Group 992

Participant:Nguyen Cong HuanNguyen Tien DucFrancesco Davide CalabreseJose Manuel González NavarroSergio Fernández Pastor

Supervisors:Hiroyuki YomoTatiana Kozlova Madsen

AbstractThe IEEE 802.11a WLAN standard and its variations arepotential candidates for an united international standard.Most of the studies on the standard have assumed error-freeor simple independent uniformly-distributed bit errors inthe channel, which does not represent the realistic usagescenarios of WLAN. In practice, WLAN connection oftenexperiences time-varying frequency-selective fading, whichnot only degrades the link quality considerably, but alsomakes its bit and packet error patterns more complicated.In this project, we develop a simulator to analyse exten-sively the performance of the IEEE 802.11a standard underfrequency-selective fading conditions.

The IEEE 802.11a provides eight dierent data rates,which can be used for link adaptation. Link adaptation,which selects the most appropriate data rate for transmis-sion according to instantaneous channel conditions, is oneof those techniques to reduce the negative eects of channelfading. Using our simulator, we analyse the performance ofa simple, but powerful, link adaptation mechanism underpractical channel models. We also examine the eects ofits parameters and propose possible modications to theoriginal scheme.

Publications: 9Number of pages: 127Finished: the 2nd of January 2004

This report must not be published or reproduced without permission from the project groupCopyright c© 2003-2004, Project Group Mob992, Aalborg University

PrefaceThis report is written during the project period of the 9th semester at the Departmentof Communication Technology, Institute of Electronic Systems, Aalborg University.

Report Structure

The report documents the implementation, results, analyses and conclusions of ourproject. Its content is, therefore, divided into 5 parts:

• Chapter 1: Background of the project

• Chapter 2: The wireless channel

• Chapter 3: The IEEE 802.11a PHY and MAC layers

• Chapter 4: Implementation and result analysis

• Chapter 5: Conclusions and future works

Acknowledgements

We would like to express our special thanks to our supervisors, Hiroyuki Yomo andTatiana Kozlova Madsen, for their thorough assistance and guidance during this project.

Nguyen Cong Huan Nguyen Tien Duc

Francesco Davide Calabrese Jose Manuel González Navarro

Sergio Fernández Pastor

i

Contents

1 Background of the project 11.1 Introduction to WLAN . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

1.1.1 Advantages and disadvantages of WLAN . . . . . . . . . . . . . . 11.1.2 WLAN standards . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

1.2 Scope of the project . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51.2.1 Problem denition . . . . . . . . . . . . . . . . . . . . . . . . . . 51.2.2 Objectives of the project . . . . . . . . . . . . . . . . . . . . . . . 8

1.3 Summaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8

2 The wireless channel 112.1 The AWGN channel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112.2 Characterisation of wireless channel . . . . . . . . . . . . . . . . . . . . . 12

2.2.1 Path loss . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122.2.2 Large-scale fading . . . . . . . . . . . . . . . . . . . . . . . . . . . 142.2.3 Small-scale fading . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

2.3 Multi-path propagation and small-scale fading . . . . . . . . . . . . . . . 142.3.1 Parameters of multi-path channel . . . . . . . . . . . . . . . . . . 172.3.2 Slow vs. fast fading . . . . . . . . . . . . . . . . . . . . . . . . . . 192.3.3 Flat vs frequency-selective fading . . . . . . . . . . . . . . . . . . 19

2.4 Summaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23

3 The IEEE 802.11a PHY and MAC layers 253.1 Description of the IEEE 802.11a PHY layer . . . . . . . . . . . . . . . . 25

3.1.1 802.11a PHY framing format . . . . . . . . . . . . . . . . . . . . 253.1.2 Implementation of IEEE 802.11 PHY . . . . . . . . . . . . . . . . 27

3.2 Description of IEEE 802.11 MAC layer . . . . . . . . . . . . . . . . . . . 343.2.1 802.11 MAC framing formats . . . . . . . . . . . . . . . . . . . . 353.2.2 Distributed Coordination Function . . . . . . . . . . . . . . . . . 36

3.3 Summaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43

iii

iv CONTENTS

4 Implementation and result analysis 454.1 The implementation of IEEE 802.11a simulator . . . . . . . . . . . . . . 45

4.1.1 The PHY layer simulator . . . . . . . . . . . . . . . . . . . . . . . 454.1.2 The MAC layer simulator . . . . . . . . . . . . . . . . . . . . . . 474.1.3 Choice of simulation parameters . . . . . . . . . . . . . . . . . . . 494.1.4 Simulation scenarios . . . . . . . . . . . . . . . . . . . . . . . . . 51

4.2 Analysis of simulation results . . . . . . . . . . . . . . . . . . . . . . . . 534.2.1 Performance of the IEEE 802.11a PHY layer . . . . . . . . . . . . 534.2.2 Performance of the IEEE 802.11a MAC layer . . . . . . . . . . . . 594.2.3 Performance of link adaptation mechanism . . . . . . . . . . . . . 65

4.3 Modication of link adaptation scheme . . . . . . . . . . . . . . . . . . . 724.3.1 Our proposal . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 724.3.2 Performance analysis . . . . . . . . . . . . . . . . . . . . . . . . . 73

4.4 Summaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76

5 Conclusions and future works 775.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77

5.1.1 The IEEE 802.11a PHY layer . . . . . . . . . . . . . . . . . . . . 775.1.2 The IEEE 802.11a MAC layer . . . . . . . . . . . . . . . . . . . . 785.1.3 Link adaptation scheme . . . . . . . . . . . . . . . . . . . . . . . 795.1.4 Modication of link adaptation scheme . . . . . . . . . . . . . . . 80

5.2 Future works . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80

Bibliography 81

A List of symbols 83

B List of acronyms 87

C The principles of OFDM technique 93C.1 The block diagram of OFDM system . . . . . . . . . . . . . . . . . . . . 96C.2 Consideration of OFDM parameters . . . . . . . . . . . . . . . . . . . . . 98C.3 Advantages and disadvantages of OFDM technique . . . . . . . . . . . . 98

D Wireless environments in PHY simulation 101

E Flowcharts of simulation functions 107

List of Figures

1.1 Classication of packet combining techniques . . . . . . . . . . . . . . . . 6

2.1 The AWGN channel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112.2 Characteristics of AWGN channel . . . . . . . . . . . . . . . . . . . . . . 122.3 A typical plane wave incident on a MS receiver [11] . . . . . . . . . . . . 152.4 Example of an indoor power delay prole; rms delay spread, mean excess

delay, maximum excess delay (at 10dB) and threshold level are shown [21] 182.5 Classications of small-scale fading channel [21] . . . . . . . . . . . . . . 202.6 The baseband representation of at fading channel . . . . . . . . . . . . 212.7 The Rayleigh and Ricean distributions . . . . . . . . . . . . . . . . . . . 222.8 The baseband representation of frequency-selective fading channel . . . . 23

3.1 Format of the 802.11a PHY frame [2] . . . . . . . . . . . . . . . . . . . . 263.2 Simplied block diagram for the 802.11a transmitter and receiver . . . . 273.3 The block diagram of the convolutional encoder used in IEEE 802.11a [2] 283.4 The puncturing patterns used in IEEE 802.11a: (a) for 3/4 rate, and (b)

for 2/3 rate convolutional code [2] . . . . . . . . . . . . . . . . . . . . . . 283.5 The constellations of BPSK, QPSK, 16-QAM and 64-QAM dened in

IEEE 802.11a standard [2] . . . . . . . . . . . . . . . . . . . . . . . . . . 313.6 The MAC frame formats [3]: (a) Data frame, (b) ACK and CTS frame,

and (c) RTS frame . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 363.7 MAC architecture [3] . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 373.8 The IEEE 802.11 Inter-Frame Spacings . . . . . . . . . . . . . . . . . . . 383.9 The random backo mechanism . . . . . . . . . . . . . . . . . . . . . . . 393.10 The exponential increase of contention window . . . . . . . . . . . . . . . 403.11 The Basic Access Method . . . . . . . . . . . . . . . . . . . . . . . . . . 413.12 The RTS/CTS Access Mode . . . . . . . . . . . . . . . . . . . . . . . . . 423.13 Hidden terminal problem and RTS/CTS access method . . . . . . . . . . 43

4.1 The block diagram of PHY layer simulator . . . . . . . . . . . . . . . . . 464.2 The state-machine diagram for an IEEE 802.11a station in passive mode 474.3 The state-machine diagram for an IEEE 802.11a station in active mode

(basic access mode) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 484.4 The state-machine diagram for an IEEE 802.11a station in active mode

(RTS/CTS access mode) . . . . . . . . . . . . . . . . . . . . . . . . . . . 484.5 The PDPs of various environments . . . . . . . . . . . . . . . . . . . . . 514.6 (a) Simulation scenario I, and (b) Scenario II . . . . . . . . . . . . . . . . 52

v

vi LIST OF FIGURES

4.7 Illustration of terminology applied for trac process[1] . . . . . . . . . . 534.8 The uncoded BER of BPSK under various environments . . . . . . . . . 544.9 The uncoded PER for BPSK under various environments . . . . . . . . . 554.10 The convolutional coded PER under various environments (Rate Index

= 1) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 554.11 The convolutional coded PER under various environments (Rate Index

= 8) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 564.12 The convolutional coded PER for dierent data rates . . . . . . . . . . . 574.13 The uncoded BER of BPSK for dierent packet sizes . . . . . . . . . . . 584.14 Total goodputs for dierent data rates (basic access method, environment

A) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 594.15 The probabilities of packet errors for dierent data rates (basic access

method, environment A) . . . . . . . . . . . . . . . . . . . . . . . . . . . 604.16 The probabilities of collision for dierent data rates (basic access method,

environment A) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 614.17 The mean transfer delay for dierent data rates (basic access method,

environment A) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 624.18 Total goodputs for dierent data rates (RTS/CTS access method, envi-

ronment A) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 624.19 The mean transfer delay for dierent data rates (RTS/CTS access

method, environment A) . . . . . . . . . . . . . . . . . . . . . . . . . . . 634.20 Total goodput at simulation scenario II (Environment A) . . . . . . . . . 644.21 Probability of collision at simulation scenario II (Environment A) . . . . 644.22 Total goodputs in environment A and E . . . . . . . . . . . . . . . . . . 654.23 Total goodput of link adaptation for basic access method . . . . . . . . . 664.24 Total goodput of link adaptation for handshaking access method . . . . . 674.25 Probability of collision of link adaptation for basic access method . . . . 684.26 Transfer delay of link adaptation for basic access method . . . . . . . . . 694.27 Transfer delay of link adaptation for handshaking access method . . . . . 694.28 Average goodput of link adaptation for basic access method . . . . . . . . 704.29 Average goodput of link adaptation for handshaking access method . . . 714.30 Goodput for link adaptation with and without data rate 7 . . . . . . . . 724.31 Proposed modication of the link adaptation scheme . . . . . . . . . . . 734.32 Total goodput for modied link adaptation scheme . . . . . . . . . . . . 744.33 Average goodput for modied link adaptation scheme . . . . . . . . . . . 754.34 Average transfer delay for modied link adaptation scheme . . . . . . . . 75

C.1 The spectrums of (a) conventional FDM and (b) OFDM technique . . . . 94C.2 Block diagrams of (a) OFDM modulator and (b) OFDM demodulator . . 95C.3 Block diagrams of OFDM system based on IFFT/FFT technique . . . . 96

LIST OF FIGURES vii

C.4 The eect of guard time between OFDM symbols: (a) Without guardtime, and (b) With guard time . . . . . . . . . . . . . . . . . . . . . . . . 97

C.5 The cyclic prex insertion and windowing processes . . . . . . . . . . . . 97

E.1 The Random sequence generator . . . . . . . . . . . . . . . . . . . . . . . 108E.2 Binary converter module . . . . . . . . . . . . . . . . . . . . . . . . . . . 108E.3 Convolutional coder module . . . . . . . . . . . . . . . . . . . . . . . . . 109E.4 Interleaving module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 110E.5 Symbol mapping module . . . . . . . . . . . . . . . . . . . . . . . . . . . 111E.6 Symbol mapping module . . . . . . . . . . . . . . . . . . . . . . . . . . . 112E.7 Symbol mapping module . . . . . . . . . . . . . . . . . . . . . . . . . . . 113E.8 Symbol mapping module . . . . . . . . . . . . . . . . . . . . . . . . . . . 114E.9 The Serial to parallel converter . . . . . . . . . . . . . . . . . . . . . . . 115E.10 The IFFT module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116E.11 The Parallel to serial module . . . . . . . . . . . . . . . . . . . . . . . . . 116E.12 Wideband channel module . . . . . . . . . . . . . . . . . . . . . . . . . . 117E.13 Wideband channel module . . . . . . . . . . . . . . . . . . . . . . . . . . 118E.14 Ricean Simulator module . . . . . . . . . . . . . . . . . . . . . . . . . . . 119E.15 AWGN channel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120E.16 FFT module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121E.17 Symbol demapping module . . . . . . . . . . . . . . . . . . . . . . . . . . 122E.18 Symbol demapping module . . . . . . . . . . . . . . . . . . . . . . . . . . 123E.19 Symbol demapping module . . . . . . . . . . . . . . . . . . . . . . . . . . 124E.20 Deinterleaving module . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125E.21 Viterbi decoder module . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126E.22 Viterbi decoder module (cont) . . . . . . . . . . . . . . . . . . . . . . . . 127E.23 Coded bit error counter . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127

List of Tables

2.1 Path loss exponents for dierent environments [21] . . . . . . . . . . . . . 13

3.1 Rate-dependent parameter [2] . . . . . . . . . . . . . . . . . . . . . . . . 323.2 Modulation-dependent normalization factor KMOD [2] . . . . . . . . . . . 323.3 Timing-related parameters in IEEE 802.11a PHY layer [2] . . . . . . . . 333.4 Timing-related parameters in IEEE 802.11a MAC layer . . . . . . . . . . 41

4.1 Parameters for PHY and MAC layer simulations . . . . . . . . . . . . . . 504.2 Channel models for PHY layer simulation . . . . . . . . . . . . . . . . . 50

D.1 Model A. Corresponds to a typical oce environment for NLOS condi-tions and 50ns average rms delay spread . . . . . . . . . . . . . . . . . . 101

D.2 Model B. Corresponds to typical large open space and oce environmentsfor NLOS conditions and 100ns average rms delay spread . . . . . . . . . 102

D.3 Model C. Corresponds to a typical large open space environment forNLOS conditions and 150ns average rms delay spread . . . . . . . . . . . 103

D.4 Model D. Same as model C but for LOS conditions. A 10 dB spike atzero delay has been added resulting in a rms delay spread of about 140ns 104

D.5 Model E. Corresponds to a typical large open space environment forNLOS conditions and 250ns average rms delay spread . . . . . . . . . . . 105

ix

Chapter

1Background of the project

1.1 Introduction to WLAN

Wireless communication has become very popular in the last few decades. It is nowpossible to communicate while being mobile, in almost all areas of the globe if one con-siders satellite communications. Since the early 80's, when the Global System for Mobilecommunication (GSM) was developed, digital mobile communications have succeededin replacing the xed phones, and it has penetrated the global market like no otherproduct ever. Since then, mobile communications have advanced into a more uniedservice to satisfy most, if not all, communication needs of human being.Now the same tendency has happened with computer communications. New wirelesstechnologies, which can provide high bandwidth to users within a limited geographicalarea, have been developed to substitute the wired Local Area Network (LAN). Followingthe success story of the mobile phone, the Wireless Local Area Network (WLAN) isexperiencing dramatic growth in the recent years. According to IDC (www.idc.com),the worldwide revenue of WLAN equipment in 2001 reached USD 1.45 billion, up 34.2%from 2000, and is expected to grow to USD 3.72 billion in 2006. One potential marketof the WLAN technologies is hot spot business, in which it is used to oer Internetconnections at public places, such as hotels, airports, train stations and cafes. Analysys,the global advisor on telecoms and new media (www.analysys.com), forecasts there willbe more than 20 millions users of public WLAN services in Europe by 2006, generatingover EUR 3 billion of revenue for hot spot operators.

1.1.1 Advantages and disadvantages of WLAN

The WLAN technologies are so successful because it oers several advantages comparedto the wired LAN:

• Ease and speed of deployment: Many areas are dicult for deploying the tra-ditional wired LAN. For example, running cables through walls of an old stonebuilding to which the layouts have been lost can be a tough challenge. Even inmodern facilities, contracting for cable installation can be expensive and time-consuming. The WLAN removes the need of cable installation, and thus it is farquicker and more convenient to deploy than the wired LAN.

1

2 Background of the project

• Flexibility: No cables means no re-cabling. The WLAN allows users to conve-niently move their network computers from one place to another, and to quicklyform small networks for meeting or group works. The WLAN also makes networkexpansion much easier, as the network medium is virtually ready everywhere. Thisis the key driving force for WLAN to succeed in the hot spot market. In ad-dition, group of WLAN devices can form an ad-hoc network, in which they canshare resources amongst each other (peer-to-peer network) without the need of aninfrastructure, and therefore allows communications even in case of disasters.

• Mobility: The WLAN allows users to stay connected while they are roaming. En-abling users to access data while they are in motion can lead to large productivitygains.

Besides its advantages, the WLAN does have some drawbacks. First of all, the costs ofWLAN components, such as adapter or Access Point (AP), are often higher than thoseof the wired LAN. However, this extra cost can be justied if we consider the price forcable installation and the productivity gains from the usage of WLAN. Moreover, theprice of WLAN gear has recently declined and will continue to fall dramatically.Secondly, the WLAN is more prone to security issues than wired LAN, as it is easierto eavesdrop an open wireless connection. Several approaches have been employed toincrease security level of the WLAN connections. For example, the Institute of Electricaland Electronic Engineers (IEEE) has dened the Wired Equivalent Privacy (WEP)standard as a security measure in its 802.11 WLAN standard, which is discussed in thenext section. However, the WEP only provides minimal protection to frames in the air,and it can be completely broken by method described by Scott Fluhrer, Itsik Mantinand Adi Shamir [6]. At the moment, the IEEE 802.11 working group has devoted anentire task group to security, which is actively working on a revised security standard.In the meantime, if high level of security is required in 802.11 system, users will have togo for proprietary approaches, but these are a single-vendor solution and only a stopgap.Thirdly, WLAN could not provide data rate as high as that of the wired LAN operatingon high-bandwidth low-loss cables. The wireless channel is fundamentally dierent fromcoaxial cable, in the following aspects:

• The allowable bandwidth for transmission is limited, because the Radio Frequency(RF) spectrum is a scarce and expensive resource.

• Due to path loss, transmitted signal is attenuated much faster in wireless channel.

• Propagation phenomena, such as large- and small-scale fading, are inevitable inwireless medium. They induce time-varying amplitude and phase changes to thereceived signals, making it more dicult to correctly decode the information.

1.1 Introduction to WLAN 3

• The transmitted signals are unprotected from outside signals.

These factors often limits the maximum achievable data rate of WLAN system. Cur-rently, various techniques are employed at both Physical Layer (PHY) and Medium Ac-cess Control (MAC) layers of WLAN system, aiming at mitigating the negative eectsof the wireless medium and making the best use of the allowable bandwidth. Never-theless, searches are still going on to nd mechanisms which could improve further theperformance of WLAN system.

1.1.2 WLAN standards

In early beginning, all WLAN solutions were proprietary, and devices from dierentvendors could not talk to each other. This incompatibility issue was the main barrierto the growth of WLAN. Today, various WLAN standards are available, which allowsWLAN devices to inter-connect from anywhere within an oce building, campus, or theconner cafe, even if they are not from the same vendor. In this section, we discuss allthe WLAN standards that are commonly-used in the market.

The HIPERLAN standard

In 1992, the European Telecommunications Standards Institute (ETSI) formed a com-mittee to establish a WLAN standard for Europe, which is referred to as the HIghPErformance Radio LAN (HIPERLAN). There are two versions of the HIPERLANstandards, which are HIPERLAN/1 and HIPERLAN/2.

The HIPERLAN/1 standard was ratied in early 1996 and oers wireless communicationwith maximum data rate of 20Mbps at the 5GHz band. It uses Gaussian Minimum ShiftKeying (GMSK) modulation which also has been adopted in the GSM cellular system.However, owing to the complexity of implementation and the huge processing powerrequired, HIPERLAN/1 is seldom used commercially.

Following the HIPERLAN/1 standard, HIPERLAN/2 specications were started in mid-1998 and the rst specications were published in 2000. It operates at data rate up to54Mbps, based on Orthogonal Frequency Division Multiplex (OFDM) technique, in thesame RF band as the HIPERLAN/1, and provides very good Quality of Service (QoS)support. Its aim is to be able to work with dierent core networks, especially thethird-generation (3G) cellular systems [26].


The MMAC-HiSWAN standard

The Multimedia Mobile Access Communication (MMAC) system was developed inJapan since 1996, which aims at to transmit ultra high speed, high quality Multi-media Information anytime and anywhere with seamless connections to optical brenetworks. The MMAC-HiSWAN (High Speed Wireless Access Network) system usestwo frequency bands: 5 GHz for HiSWANa and 25 GHz for HiSWANb. This standardis closely aligned with the ETSI HIPERLAN/2 standard. The HiSWANa specicationadopts the OFDM physical layer providing a standard speed of 27Mbps and 6-36Mbpsby link adaptation. However, there are some dierences between MMAC-HiSWANaand ETSI HIPERLAN in radio network functions, owing to the dierences in regionalfrequency planning and regulations [26].

The 802.11 standard

Adopted by the IEEE in 1997, the 802.11 has become the rst international standardfor WLAN and it has been used widely in most commercial WLAN products availablein the market. The IEEE 802.11 species how wireless network devices communicatewith one another, and it serves as foundation to establish wireless networking standardsincluding:

• The IEEE 802.11a describes the wireless networking standard that operates inthe 5GHz radio band (Unlicensed - National Information Infrastructure (U-NII)frequency band) using OFDM technique. The IEEE 802.11a-based WLANs canachieve a maximum data rate of 54Mbps, providing nearly ve-times faster net-working data rate than IEEE 802.11b and can handle more trac than 802.11b-based networks.

• The IEEE 802.11b, commonly known as Wi-Fi, was the rst WLAN technologyoered to consumers. It operates in the 2.4GHz radio band (Industrial, Scienticand Medical (ISM) frequency band) using either Direct Sequence Spread Spectrum(DSSS) or Frequency Hopping Spread Spectrum (FHSS) technique. The 802.11bcan achieve a maximum data rate of 11Mbps at distance up to approximately 90meters (or 300 feet). Thanks to its early presence, the 802.11b devices are farmore common than any other WLAN standards.

• The IEEE 802.11g is a new standard, describing a wireless networking method forWLANs that operates in 2.4GHz radio band. By using OFDM technique, 802.11g-based WLANs can achieve maximum data rate of 54Mbps. The IEEE 802.11g-compliant equipment, such as wireless AP, may provide simultaneous WLAN con-nectivity for both 802.11g and 802.11b equipment. It was designed largely as areaction to the regulatory environment in some countries, and a variety of inght-ing and conict made this a compromise standard.

1.2 Scope of the project 5

• The IEEE 802.11h is another variation on the 802.11a, which specically aims atsatisfying European regulations for 5GHz WLANs. European radio regulations forthe 5GHz band require products to have Transmission Power Control (TPC) andDynamic Frequency Selection (DFS), which are not available in 802.11a. The IEEE802.11h is designed to provide these additional features to 802.11a standard [8].

The fact that there are so many standards available to public makes inter-operationbetween WLAN devices dicult. Currently, the IEEE 802.11a and its variations arepromising candidates for unied international standard. Therefore, in this project, ourfocus is on the IEEE 802.11a standard.

1.2 Scope of the project

1.2.1 Problem denition

As mentioned in section 1.1.1, the performance of the IEEE 802.11a standard is limitedmainly due to channel impairment. In recent years, much interest has been involved innding new techniques to improve this situation. Here, we focus on two main techniquesthat are currently receiving a lot of attentions: Packet combining and Link adaptation.

Packet combining techniques

In order to maintain reliable and ecient communication over noisy channel, the IEEE802.11a standard species a hybrid Forward Error Correction (FEC) and AutomaticRepeat Request (ARQ) for its transmission. The ARQ system provides the very lowundetected error probability performance required, while the FEC system reduces thenumber of re-transmission by correcting as many packets in error as possible. In thisFEC/ARQ scheme, the receiver discards erroneous packet that cannot be corrected bythe FEC, and wait for re-transmission. Packet decoding is performed using only a singlecopy of re-transmitted packet and ignores the information contained in all previouscopies. This is often referred to as Hybrid Type-I ARQ scheme. When channel becomesvery noisy, it is possible that all packets contains uncorrectable errors. In this case, suchsystem fails to provide a signicant throughput [16].The basic idea behind packet combining is that a received packet always contains at leasta small amount of useful information which can be exploited. Thus, packet decodingis more likely to succeed if the useful information contained in all previous copies of apacket is used. By combining the erroneous packets in an optimum manner, signicantdata throughput is obtained even when the Type-I ARQ approach of just repeatingpackets fails [4].


Selectioncombining

Maximal ratiocombining

Equal gaincombining

Packet combining

Diversity combining

Hybrid−ARQ type II Hybrid−ARQ type III

Code combining

Figure 1.1: Classication of packet combining techniques

Figure 1.1 shows the classication of packet combining techniques. The most commonly-used packet combining technique is diversity combining. In diversity combining, thesymbols of all received copies of a packet are added up and that sum is decodedby the receiver. Diversity combining can be divided further into Selection Combining(SC), Equal Gain Combining (EGC) and Maximal Ratio Combining (MRC), dependingon which technique is employed for combining the symbols. Diversity combining isrelatively simple to implement in IEEE 802.11a device, as it requires no modicationsin the standard and the structure of 802.11a device allows the use of diversity combiningwithout considerable increase in complexity. However, diversity combining requires thatthere is very low, ideally zero, level of cross-correlation between two or more copies ofthe same packet. If the wireless channel varies at very slow rate compared to the packettransmission rate, the system will not benet from diversity combining.The code combining was rst proposed by Chase in [4]. This technique combines allcopies of the packet at codeword level with a maximum-likelihood decoder, which repre-sents an added dimension to the above-mentioned diversity concept which is limited tocombining just individual symbols. Thus, this technique provides higher performancegain than the conventional diversity combining [4]. The idea of code combining is furtherextended in Type-II and Type-III ARQ schemes, which are pioneered by Hagenauger [14]and Kallel [15], respectively. In the hybrid Type-II ARQ schemes, which are sometimesreferred to as incremental redundancy ARQ, the transmitter starts with the highestrate code of the Rate-Compatible Punctured Codes (RCPC) family. If the rst trans-mission fails, the transmitter continues to send incremental code bits until the packet isreceived correctly. The main drawback of incremental redundancy ARQ scheme is thatadditional incremental code bits sent for a packet received with errors (or a packet thatis lost) are not in general self-decodable. That is the decoder must rely on both theinitially transmitted packet as well as the additional incremental code bits for decoding.The Type-III ARQ scheme presents a dierent class of punctured convolutional codes,namely Complementary Punctured Codes (CPC) codes. The main advantage of usingthe CPC codes is that any complementary sequence sent for a packet that is lost or de-tected with errors is self-decodable, and the receiver does not have to rely on previously

1.2 Scope of the project 7

received sequences for the same data packet for decoding.The impact of code combining on overall IEEE 802.11a performance is not well under-stood, and therefore should be investigated more carefully before it can be applied inthe standard. Furthermore, implementation of Type-II or Type-III ARQ schemes in theIEEE 802.11a would require modications of this standard (i.e. to introduce the RCPCor CPC codes).

Link adaptation techniques

In general, the principle of link adaptation technique is to vary dierent parameters ofWLAN system, such as transmitting power, data rates (i.e. coding and modulationschemes) and packet sizes, according to the simultaneous quality of the radio link inorder to obtain the maximum available throughput. However, in this project, we limitsthe link adaptation technique to only one parameter: the data rate. The idea of linkadaptation, in this sense, is to choose the most appropriate transmission mode accordingto channel conditions.The IEEE 802.11a supports eight dierent data rates, from 6 to 54Mbps with dierentcoding and modulation schemes. While the data rates for link adaptation scheme aredened, the actual link adaptation algorithm is left open. As a result, there are many linkadaptation proposals for the IEEE 802.11a. For example, a best PHY mode table isused to nd the suitable data rate according to packet size, Signal to Noise Ratio (SNR)value and frame retry count in [20]. This method is relatively complicated, becauseit requires the estimation of SNR of transmission link. Besides, the best PHY modetable might not be valid for all types of channel models, which could induce negativeeects to the performance of WLAN system operating on dierent types of channels.Another simpler, but not less powerful, link adaptation method is proposed in [5]. Themethod is similar to the Auto-Rate Fallback (ARF) method used in Lucent's WaveLAN-II device [17]. The transmitter maintains two counters for each of its links, one forsuccessful transmission and one for failed transmission. If a packet is transmitted suc-cessfully, the success counter is increased by one, and the failure counter is reset to zero.On the other hand, if the transmission fails, then the failure counter is incremented byone and the success counter is reset to zero. If the success counter is greater than athreshold value S, then the the transmitter will start the next transmission using thenext (i.e. higher) data rate available. Similarly, if number of packet failed is greaterthan the threshold F , the transmission rate is decreased by one. All the counters arereset to zero after the transmission rate changed.The performance and eciency of this link adaptation method depends on the choicesof S and F . The performance of several values of S have been studied in [5] usingnarrowband Rayleigh channel. However, this type of channel cannot represent the real


usage scenario of the WLAN in which the channel usually suers from frequency-selectivefading.

1.2.2 Objectives of the project

In this project, we choose to investigate the link adaptation scheme proposed in [5]. Thisis a promising technique for lling in the link adaptation vacancy in the IEEE 802.11astandard. It is very simple to implement, and able to provide considerable gain in systemthroughput [5]. However, the performance of this scheme must be well-understood beforeit can be applied in practice.Under the title Link adaptation for IEEE 802.11a WLAN over fading channel ,this project aims at two main objectives:

• To analyse the performance of the IEEE 802.11 MAC layer under realistic channelconditions. Most of the researches have assumed error-free or simple independentuniform bit errors in the channel for their 802.11a studies. These simple assump-tions are not very realistic, since the WLAN connection often experiences time-varying frequency-selective fading, which makes its bit and packet error patternsmore complicated. In this project, we develop an IEEE 802.11a simulator oper-ating on frequency-selective channel models, which are abstracted from practicalmeasurements. The average goodput, which is dened as the ratio between totalnumber of information bits received at the destination and the total time neededfor transmission, is the main parameter to be calculated and analysed in the sim-ulation. Additional parameters, such as the mean transfer delay and collisionprobability are also obtained and discussed.

• To validate the performance of link adaptation method in [5] with realistic channelmodels. A simple Rayleigh at fading channel model is used in [5], which doesnot represent a practical scenario. In this project, the above-mentioned IEEE802.11a simulator and frequency-selective fading channel models are employed tovalidate the performance of the proposed scheme. We also examine the eectsof its parameters (S and F ), and discuss possible modications to the originalscheme.

1.3 Summaries

This chapter serves as an introduction to our 9th semester project at Aalborg University.In this chapter, we have discussed the growth of WLAN, its advantages and disadvan-tages, together with short introduction of dierent WLAN standards.

1.3 Summaries 9

In this project, our focus is on the IEEE 802.11a, a promising candidate to be theunied international WLAN standard. Several mechanisms, which can help to improvethe performance of IEEE 802.11a, are briey discussed in this chapter.The objectives of this project are: (a) To analyse the average goodput of the IEEE 802.11MAC layer under realistic channel conditions, and (b) To validate the performance oflink adaptation method proposed in [5]. To help unfamiliar readers understand ourworks, we are going to present some introduction of wireless channel, and IEEE 802.11PHY and MAC layers in the following chapters.

Chapter

2The wireless channel

The wireless channel is a medium that exists between two end points of any wirelesscommunication system. It has great impact on the performance of the wireless commu-nication system. The system designer often has no control on the choice of channel, andin most cases, the system design has to compensate for the channel impairment. It isvery important for the system designer to be able to know most or some of the prop-erties of the channel before design of the system begins. That can either be achievedwith extensive channel measurements at the area where the link is deployed, or withchannel models that can characterise these channels in some extents. In this section, weintroduce channel models that are used throughout our project.

2.1 The AWGN channel

The most well-known and widely-used model in digital communications is the AdditiveWhite Gaussian Noise (AWGN) channel, which is illustrated in Figure 2.1. The AWGNchannel model is useful for verifying the performance of wireless communication systems:it approximates the performance of the wired channel and serves as the lower bound forthe degradation by the radio channel [10].

Figure 2.1: The AWGN channel

In an AWGN channel, the transmitted signal r(t) gets disturbed by an additive whiteGaussian noise process n(t) and the received signal s(t) is given in equation (2.1):

s(t) = r(t) + n(t) (2.1)

11

12 The wireless channel

Typical characteristics of the white Gaussian noise n(t) are: (a) Any two noise samplesare statistically independent and its Auto-Correlation Function (ACF), Rn(τ), consistsof a weighted delta function:

Rn(τ) =N0

2δ(τ) (2.2)

and (b) Its Power Spectral Density (PSD) is a constant over all frequency of interest.

Sn(f) =N0

2(2.3)

The latter two characteristics are depicted in Figure 2.2 (a) and (b) respectively.

Figure 2.2: Characteristics of AWGN channel

Although the AWGN channel often serves as a reference channel model in wirelesscommunication systems, it is not sucient to describe real characteristics of a wirelesschannel, such as shadowing or multi-path fading phenomenon. We will go through themain phenomena of the wireless channel in the next section.

2.2 Characterisation of wireless channel

To understand how radio channel can aect the operations of mobile communicationsystems, we need to understand its behaviours. These behaviours can be divided intothree categories: path loss, large-scale fading and small-scale fading.

2.2.1 Path loss

The path loss is the signal attenuation caused by beam divergence, i.e. signal energyspreads over larger areas at increased distances from the source. If we consider a mobilecommunication system working in idealised free space, where there is no object thatmight absorb or reect RF energy and the atmosphere behaves as a perfectly uniform

2.2 Characterisation of wireless channel 13

and non-absorbing medium, the RF energy between the transmitter and the receiverreduces according to an inverse-square law with distance. When the received antennais isotropic, the attenuation factor Lfs(d), sometimes referred to as free-space loss, canbe expressed as [22]:

Lfs(d) =Pr(d)

Pt

=

(4πd

λ

)2

(2.4)

where Pt is the transmitted power, Pr(d) is the received power at distance d, and λ isthe wavelength of the propagating signal.

Instead of using the transmitted power as in equation (2.4), large-scale propagationmodels often use a close-in distance, d0, as a known received power reference point tocalculate the path loss. Then, the free-space path loss at any distance d, PLfs(d), isgiven by:

PLfs(d) =Pr(d)

Pr(d0)=

(d

d0

)2

(2.5)

In general, if the transmitter and the receiver are not in idealised free space, the pathloss is usually increasing with nth power of the distance between them [21]:

PL(d) ∝(

d

d0

)n

(2.6)

where PL(d) is the path loss as a function of distance d, and n is environment-dependentpath loss exponent which indicates the rate at which the path loss increases with dis-tance. For instance, the Table 2.1 provides the measured path loss exponents for variousenvironments.

Table 2.1: Path loss exponents for dierent environments [21]

Environment Path Loss Exponent (n)Free space 2Urban area cellular radio 2.7 to 3.5Shadowed urban cellular radio 3 to 5In building Line Of Sight (LOS) 1.6 to 1.8Obstructed in building 4 to 6Obstructed in factories 2 to 3


2.2.2 Large-scale fading

The large-scale fading is due to motion of the mobile receiver over large terrain obstacles(such as hills, buildings, etc.) between the transmitter and the receiver. The receiveris often represented as being shadowed by such obstacles, which causes the receivedsignal power to drop for a period of time. Measurements have shown that at any valueof distance d, the path loss PL(d) is random and log-normally distributed (i.e. normalin dB) about the mean distance-dependent value [21]:

log

PL(d)

= log

PL(d)

+ Xσ (2.7)

where Xσ is a zero-mean Gaussian distributed random variable (in dB) with standarddeviation σ (also in dB).The large-scale fading is also referred to as slow fading, as it varies slowly over time(over 20-30 wavelengths).

2.2.3 Small-scale fading

The small-scale fading phenomenon refers to the dramatic changes in signal amplitudeand phase due to the combination of multi-path signals at the receiver. It is one of thekey subjects in our project and deserves to be discussed separately in the next section.

2.3 Multi-path propagation and small-scale fading

Multi-path propagation occurs when a transmitted signal, which is diracted, reectedand scattered from surfaces of obstacles, such as buildings, walls or trees, arrives at areceiver from dierent paths. These multi-path components, with random phases andamplitudes, combine vectorially at the receiver, causing amplitude and phase of receivedsignal to uctuate. As the carrier wavelength used in Ultra High Frequency (UHF)mobile radio applications ranges from 15 to 60cm, a very small change (as small as ahalf-wavelength) in the spatial separation between receiver and transmitter can causelarge change in the phases of multi-path components. As a result, the uctuation inreceived signal is much faster than in the case of large-scale fading. Hence, it is oftenreferred to as small-scale fading or fast fading.The small-scale fading channel is often characterised by Clarke's 2D model. The modelconsiders a xed transmitter communicating with a mobile receiver, both of which havingvertically polarised antennas. In order to reduce complexity, Clarke's 2D model assumesthat the distance between the transmitter and the receiver is suciently large, so thatthe radio propagation environment can be modelled in two dimensions, i.e. all incoming

2.3 Multi-path propagation and small-scale fading 15

waves travel in the azimuthal plane. This assumption has been proved to be practical,because many measurements observed in reality show similar Doppler spectrum shapeas one predicted by Clarke [19]. Based on the above-mentioned assumption, the incidentwaves at the mobile receiver can also be seen as plane waves.

thn incoming wave

θn

Mobile x

y

v

Figure 2.3: A typical plane wave incident on a MS receiver [11]

Figure 2.3 depicts a mobile receiver moving along the x-axis with velocity v. At anytime, there are a number of incoming waves arriving at the receiver, with dierent delaysand Angle of Arrival (AoA). Let's take a look at the nth incoming wave, which arrivesat angle θn. The Doppler shift, or frequency shift, fD,n associated with that incomingwave can be calculated as follows:

fD,n = fm cos θn [Hz] (2.8)

where fm = vλis the maximum Doppler frequency, which occurs when θn = 0o, and λ is

the wavelength of the incident waves.

The passband representation r(t) of the transmitted signal can be expressed as [23]:

r(t) = Re[r(t)ej2πfct] (2.9)

where Re[.] is the real part of the complex signal, r(t) is the complex envelope (orbaseband representation) of the transmitted signal, and fc is the carrier frequency.

At the receiver, the received signal associated with the nth incoming path is attenu-ated, delayed in time, and shifted in frequency due to Doppler phenomenon. Fromequations (2.8) and (2.9), such a signal is given as:

sn(t) = ReCn(t)ej2π(fc+fD,n)(t−τn(t))r(t− τn(t))

(2.10)


where Cn(t) and τn(t) are respectively the time-variant amplitude and the time delayassociated with the nth propagation path.

The received signal is the sum of dierent scattering paths, each possessing independentamplitude Cn(t), Doppler shift frequency fD,n and time delay τn(t). Assuming thatthere is a nite number M of scattering paths, the passband representation of receivedsignal can be expressed as [23]:

s(t) =M∑

n=1

sn(t) = Re M∑

n=1

Cn(t)ej2π(fc+fD,n)(t−τn(t))r(t− τn(t))

= Re M∑

n=1

Cn(t)e−jφn(t)r(t− τn(t))ej2πfct

(2.11)

in which:φn(t) = 2π[(fc + fD,n)τn(t)− fD,nt] (2.12)

is the phase associated with the nth incoming path.

From equation (2.11), it is obvious that the baseband representation of the receivedsignal is given as follows:

s(t) =M∑

n=1

Cn(t)e−jφn(t)r(t− τn(t)) (2.13)

Equation (2.13) shows that the noiseless multi-path channel can be modelled as a time-varying tapped delay line lter with the following impulse response:

h(t, τ) =M∑

n=1

gn(t)δ(τ − τn(t)) (2.14)

where δ(.) is Dirac delta function and gn(t) is the time-variant complex gain correspond-ing to the nth scattering path of the channel and given as:

gn(t) = Cn(t)e−jφn(t) (2.15)

If the channel is assumed to be time-invariant, or is at least Wide Sense Stationary(WSS) over a small-scale time or distance interval, the equation (2.14) is reduced to [21]:

h(τ) =M∑

n=1

Cne−jφnδ(τ − τn) =M∑

n=1

gnδ(τ − τn) (2.16)


2.3.1 Parameters of multi-path channel

In this section we will discuss several important parameters which grossly quantify theabove-mentioned multi-path channel model. First of all, we can dene excess delay asthe relative delay of the nth multi-path component as compared to the rst arrivingcomponent and is given as ∆n:

∆n = τn − τ0 (2.17)

where τ0 is the delay of the rst arriving multi-path component.The Maximum excess delay is the largest excess delay experienced in the channel:

∆max = max(∆1, ∆2, . . . , ∆M) (2.18)

Secondly, we can dene the Power Delay Prole (PDP) as the magnitude squared ofthe channel impulse response:

PDP (τ) =| h(τ) |2=M∑

n=1

| gn |2 δ(τ − τn) (2.19)

The PDP is an important parameter of the wireless channel, as it indicates the distribu-tion of received power in delay domain. For convenient, PDP (τ) normally has its timeorigin redened so as to position the rst arriving multi-path component at τ = 0, andthe function is then dened in terms of the excess delay variable ∆, i.e [19]:

PDP (∆) = PDP (τ − τ0) =M∑

n=1

| gn |2 δ(∆−∆n) (2.20)

An example of the PDP is illustrated in Figure 2.4. Two statistical moments of PDP (∆)

of practical interest are themean excess delay and the rms delay spread. The mean excessdelay, ∆, is the rst moment of the PDP and is dened to be [21]:

∆ =

∑k PDP (∆k)∆k∑

k PDP (∆k)(2.21)

The rms delay spread is the square root of the second central moment of the PDP andis dened to be [21]:

σ∆ =

√∆2 − (∆)2 (2.22)

where:∆2 =

∑k PDP (∆k)∆

2k∑

k PDP (∆k)(2.23)

Equations (2.21) and (2.22) do not rely on the absolute power level of the PDP, but onlythe relative amplitudes of the multi-path components within the PDP. Typical values


Figure 2.4: Example of an indoor power delay prole; rms delay spread, mean excess delay, maximum excess delay (at

10dB) and threshold level are shown [21]

of rms delay spread are on the order of microseconds in outdoor mobile radio channelsand on the order of nanoseconds in indoor radio channels [21]Thirdly, we can calculate the spectral response (or magnitude frequency response) of thewireless channel as the Fourier transform of the PDP:

SP (f) = FTPDP (∆)

(2.24)

where FT. denotes the Fourier transform function. The spectral response functionshows the behaviour of the wireless channel in frequency domain.Analogous to the delay spread parameters in the time domain, coherence bandwidth isused to characterised the channel in frequency domain. Coherence bandwidth, Bc, isa statistical measure of the range of frequencies over which the channel can be con-sidered at (i.e. a channel which passes all spectral components with approximatelyequal gain and linear phase). In other words, coherence bandwidth is the range of fre-quencies over which two frequency components have a strong potential for amplitudecorrelation. Two sinusoids with frequency separation greater than Bc are aected quitedierently by the channel. If the coherence bandwidth is dened as the bandwidth overwhich the frequency correlation function is above 0.5, then the coherence bandwidth isapproximately [21]:

Bc ≈ 1

5σ∆

(2.25)

It is important to note that an exact relationship between coherence bandwidth andrms delay spread does not exist, and equation (2.25) is only an estimate.


Although delay spread and coherence bandwidth describe the time dispersive natureof the small-scale fading channel, they do not oer information about the time-varyingnature of such channel caused by relative motion between the transmitter and receiver.We need another set of parameters, Doppler spread and coherence time, to do the job.The Doppler spread, BD, is a measure of the spectral broadening caused by the timerate of change of the mobile radio channel and dened as the range of frequencies overwhich the received Doppler spectrum is essentially non-zero. If a pure sinusoidal signalof frequency fc is transmitted into the channel, the received signal spectrum, calledDoppler spectrum, will have components in range of fc− fd and fc + fd, where fd is theDoppler shift. The amount of spectral broadening depends on fd, which is a function ofthe velocity of the mobile receiver and the AoA (see Figure 2.3).The coherence time, Tc, is the time domain dual of the Doppler spread and it is usedto characterise the time varying nature of the channel. In other words, it is a statisticalmeasure of the time duration over which the channel impulse response is essentiallyinvariant, and quanties the similarity of the channel response at dierent times. If thecoherence time is dened as the time over which the time correlation function is above0.5, then the coherence time is approximately [21]:

Tc ≈ 9

16πfm

(2.26)

where fm is the maximum Doppler shift.

2.3.2 Slow vs. fast fading

Depending on how rapidly the transmitted signal changes compared to the rate of changeof the channel, a small-scale fading channel can be classied as either fast fading or slowfading. In a fast fading channel, the channel coherence time, Tc, is less than symbolperiod, Ts. In other words, the channel behaviours change during one symbol duration.As the channel coherence time is inversely-proportional to the Doppler spread, BD, thefast fading channel often has high Doppler spread. In practice, fast fading only occursin transmission links with very low data rate.On the other hand, a small-scale fading channel is referred to as slow fading if the channelimpulse response remains constant during one or several symbol periods. It means thatslow fading happens when the symbol period, Ts, is smaller than the channel coherencetime, Tc; or the Doppler spread is smaller than the bandwidth of the transmitted signal.

2.3.3 Flat vs frequency-selective fading

The small-scale fading channel can also be classied by its time-dispersiveness nature. Asmall-scale fading channel is referred to as at fading if its channel coherence bandwidth,


Bc, is much larger than the bandwidth of the transmitted signal, Bs. This means thatall frequency components of the transmitted signal are undergone the same level offading and thus the spectral characteristics of the transmitted signal are preserved atthe receiver. For this reason, at fading channels are also known as narrow-band channel,since the bandwidth of the applied signal is narrow as compared to the channel atfading bandwidth.

Fast fading Slow fading

(Based on Doppler spread)

Small−Scale Fading

Small−Scale Fading(Based on multipath time delay spread)

2. Delay spread < Symbol period

1. BW of signal < BW of channel

Flat fading

2. Delay spread > Symbol period

1. BW of signal > BW of channel

Frequency Selective Fading

1. High Doppler spread

2. Coherence time < Symbol period

3. Channel variations faster than

baseband signal variations

1. Low Doppler spread

2. Coherence time > Symbol period

3. Channel variations slower than

baseband signal variations

Figure 2.5: Classications of small-scale fading channel [21]

In a at fading channel, the rms delay spread, σ∆, is much smaller than the symbolperiod, Ts. Under this assumption we can consider that the τn in the equation (2.16),which represents the time delay for the nth scattering path from the transmitter to thereceiver, is approximately equal to τc for each n. Thus we can rewrite the equation (2.16)as follows:

h(τ) = δ(τ − τc)M∑

n=1

Cne−jφn

= g(t)δ(τ − τc) (2.27)

where g(t) =∑M

n=1 Cne−jφn is the time-varying complex gain of the at fading channel.It is important to note that the impulse response of the at-fading channel is onlyone tap at τc. Without loss of generality, we can assume the time delay τc is zero, orthere is no delay occurred between the transmitter and the receiver. This assumptionis reasonable, because there are dierent synchronization techniques available to thereceiver to compensate for that time delay. In addition, the eect of thermal noise andinterference of the channel is modelled by adding AWGN channel n(t) to the receivedsignal. As a result, the baseband representation of the received signal of a at fading


channel is given as:

s(t) = h(t)⊗ r(t) + n(t)

= g(t)r(t) + n(t) (2.28)

where ⊗ denotes the convolution operation. The gure 2.6 illustrates the equivalentbaseband representation of the at fading channel.

Figure 2.6: The baseband representation of at fading channel

[11], [19] and [21] provide very detailed analysis on the characteristics of the time-varying complex gain, g(t), of the at fading channel. In absence of a LOS or dominantscattering path, the phase of the complex gain is uniformly distributed and the envelopehas Rayleigh distribution:

fΩ(r) =

rσ2Ω

exp

(− r2

2σ2Ω

)r ≥ 0

0 otherwise

(2.29)

where Ω is the short-term envelope of the complex gain and σ2Ω =

PMn=1 C2

n

2is the mean

power of the complex gain [21].On the other hand, if there is a dominant stationary (or non-fading) signal componentpresent at the receiver, such as LOS propagation path, the envelope of the complex gainhas Ricean distribution:

fΩ(r) =

rσ2Ω

exp

(− r2+A2

2σΩ

)I0

(− Ar

σ2Ω

)A ≥ 0 and r ≥ 0

0 r < 0

(2.30)

The parameter A denotes the peak amplitude of the dominant signal and I0(.) is themodied Bessel function of the rst kind and zero order. For calculation convenient,the Ricean distribution is often described in terms of a parameter K, which is denedas [21]:

K =A2

2σ2Ω

(2.31)


The Rayleigh and Ricean distributions are plotted against each other in Figure 2.7 forcomparison. We can observe that if A → 0, then K → 0 and the Ricean degenerates toa Rayleigh distribution. The Figure 2.7 also shows that, for Rayleigh or Ricean fadingwith small value of factor K, the level and the possibility to have deep fades are higherthan that of Ricean fading with large K, which results in degradation of wireless systemperformance.

0 1 2 3 4 5 6 7 80

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Ricean and Rayleigh distributions of the fading envelope (with the same mean power σΩ2 )

Pro

babi

lity

Den

sity

Fun

ctio

n

Short−term fading envelope Ω

Ricean distribution, K = 10Ricean distribution, K = 1Rayleigh distribution

Figure 2.7: The Rayleigh and Ricean distributions

In contrast to the at fading channel, frequency-selective fading channel happens if thechannel coherence bandwidth, Bc, is smaller than the bandwidth of the transmitted sig-nal, Bs. Equivalently, the rms delay spread, σ∆, is greater than the symbol period, Ts,in frequency-selective fading channel. In this case, dierent frequency components of thetransmitted signal are undergone dierent levels of fading, and the spectral characteris-tics of the transmitted signal are not preserved at the receiver. This causes distortion inthe time-domain representation of the received signal, and the channel is said to induceInter-Symbol Interference (ISI). As a result, the frequency-selective fading channel isfar worse than the at fading channel in terms of performance. It is sometimes referredto as wide-band channel, because the bandwidth of the transmitted signal is relativelywider than the coherence bandwidth of the channel.

The frequency-selective fading channel is much more dicult to model than the atfading channel and often it is established from measurements. From equation (2.16), we

2.4 Summaries 23

can derive the relationship between the transmitted and received signals in a frequency-selective fading channel as follows:

s(t) = h(t)⊗ r(t) + n(t)

=M∑

n=1

gn(t)r(t− τn) + n(t) (2.32)

The equation (2.32) shows that the impulse response of the frequency-selective fadingchannel has multiple taps at dierent delays, and each of those can be seen as one at-fading channel. As a result, the frequency-selective fading channel can be modelled asa combination of multiple at fading channels as illustrated in Figure 2.8.

Figure 2.8: The baseband representation of frequency-selective fading channel

High-speed wireless communication systems, such as WLAN, often encounter frequency-selective fading condition. Such condition induces ISI into the received signal and greatlydegrades the performance of the systems. In the Appendix C we discuss in details theOFDM technique which can help to mitigate the negative eects of the frequency-selective fading channel.

2.4 Summaries

In this chapter, we have characterized the most common propagation phenomena thatoccurred in the wireless medium. The wireless channel is often more hostile than itswired counterpart, and its behaviour is often dicult to predict. In order to analysethe capabilities of wireless communications system to cope with channel impairements,system designers often use some kind of channel models.


This chapter introduces three commonly-used channel models, namely AWGN, at fad-ing (or narrow-band) and frequency-selective fading (or wideband) channels. TheAWGN channel approximates the performance of the wired channel and serves as thelower bound for the degradation by the wireless channel. The at fading channel hap-pens when the channel coherence bandwidth is much larger than the bandwidth of thetransmitted signal. The at fading channel can cause severe fades in received signal,which considerably degrades the system performance compared to AWGN channel. Onthe other hand, the frequency-selective fading channel occurs if the channel coherencebandwidth is smaller than the bandwidth of the transmitted signal. This is the worsttype of channel models, because it induces ISI in the received signal. The frequency-selective fading channel is more dicult to model than at fading channel and oftenestablished from measurements. We will introduce several specic frequency-selectivechannel models in chapter 4.

Chapter

3The IEEE 802.11a PHY and MAC layers

3.1 Description of the IEEE 802.11a PHY layer

The IEEE 802.11a PHY layer acts as a bridge between the MAC layer and the wirelessmedium. Thus, it was designed to support two main functions, as follows:

• It denes the mechanism for transmitting and receiving data frames through awireless medium between two or more Station (STA)s. When the IEEE 802.11working group began evaluating proposals for the 802.11a, they adopted a jointproposal from NTT and Lucent that recommended OFDM as the baseline technol-ogy for the Physical Medium Dependent (PMD) system of the 5GHz WLAN. TheOFDM technique was chosen because of its superior performance in combatingfrequency selective fading (Refer to Appendix C for more information).

• It provides convergence function, which adapts the capabilities of the PMD systemto the PHY services. This function is supported by the Physical Layer ConvergenceProcedure (PLCP), which denes a method of mapping the IEEE 802.11 PHYSublayer Service Data Unit (PSDU) into a framing format suitable for sendingand receiving user data and management information between two or more STAusing the associated PMD system.

Details about the PHY functions as well as PHY services can be obtained in [2]. In thissection, we are going to present only aspects of the IEEE 802.11a PHY that are relevantto our project.

3.1.1 802.11a PHY framing format

The 802.11a PLCP transforms each data frame received from the MAC layer into aPLCP Protocol Data Unit (PPDU). As illustrated in Figure 3.1, the PPDU is dividedinto 3 main parts:

• PLCP PREAMBLE This part consists of 12 symbols and enables the receiverto acquire timing and frequency synchronization and to estimate the channel re-sponse.

25

26 The IEEE 802.11a PHY and MAC layers

Figure 3.1: Format of the 802.11a PHY frame [2]

• SIGNAL This part is always sent at the lowest rate, which is 6Mbps. It isencoded with convolutional coder at rate of R = 1/2, and subsequently mappedonto a single Binary Phase Shift Keying (BPSK)-modulated OFDM symbol. Itcontains the following elds:

Rate This eld identies the data rate used at the DATA part, and isrequired to decode this part.

Reserved This eld is reserved for future usage, and is currently set to0.

Length This eld represents the number of octets in the PSDU that theMAC is currently requesting the PHY to transmit.

Parity Based on the values of Rate, Reserved and Length elds, thiseld contains a single-bit value that provides even parity.

Tail This eld is always set to 0 to return the convolutional encoderto zero state.

• DATA This part can be sent at dierent data rates, which is indicated by theRate eld. It consists of the following elds:

Service This eld consists of rst seven bits as 0, to synchronize thedescrambler in the receiver and another nine bits (currently all 0)reserved for future usage.

PSDU This part represents the contents of the PPDU, or the actualMAC frame being sent.

Tail This eld consists of six bits (all 0) to return the convolutionalencoder to zero state.

Pad bits This eld contains number of bits in order to make the framesize equal to a specic multiple of coded bits in an OFDM symbols.

3.1 Description of the IEEE 802.11a PHY layer 27

3.1.2 Implementation of IEEE 802.11 PHY

A simplied block diagram of the transmitter and receiver for the OFDM-based 802.11aPHY is shown in Figure 3.2. In this section, each block of the diagram is discussed indetails.

Figure 3.2: Simplied block diagram for the 802.11a transmitter and receiver

Scrambler / Descrambler

According to the standard, the DATA portion is scrambled using a frame synchronuous127 bits sequence generator. Scrambling is used to randomize the Service, PSDU andpad bits, which might contain long strings of 0 and/or 1. The Tail bits are notscrambled. The frame synchronous scrambler uses the generator polynomial S(x) asfollows:

S(x) = x7 + x4 + 1 (3.1)

The same scrambler is used to scramble transmitted data and to descramble receiveddata. When a STA is transmitting, the initial state of the IEEE 802.11a scramblerwill be set to a pseudo random non-zero state. The rst seven bits of the Service eldwill be set to a zeros prior to scrambling to enable estimation of the initial state of thescrambler at the receiver. The content of the SIGNAL part of the 802.11a frame is notscrambled.

Convolutional coder and Viterbi decoder

To protect the transmitted frames from channel errors, FEC scheme is implementedin IEEE 802.11a using the convolutional encoder of rate R = 1/2. The encoder usesindustrial-standard generator polynomials, g0 = 1338 and g1 = 1718 (or equivalently0010110112 and 0011110012 in binary format). These generator polynomials dene theconnections for the output bit A and B, respectively, as shown in Figure 3.3. The bitdenoted as A is output from the encoder before the bit denoted as B.The number of shift register elements determines how large a coding gain the convolu-tional code can achieve. The longer the shift register, the more powerful the code is.However, the decoding complexity of the maximum likelihood Viterbi algorithm grows


Figure 3.3: The block diagram of the convolutional encoder used in IEEE 802.11a [2]

Figure 3.4: The puncturing patterns used in IEEE 802.11a: (a) for 3/4 rate, and (b) for 2/3 rate convolutional code [2]


exponentially with the number of shift register elements. This limits the currently usedconvolutional codes to maximum eight shift register elements, and IEEE 802.11a usesonly six, due to its very high speed data rate [9].

In IEEE 802.11a specications, additional rates of 2/3 and 3/4 can be achieved bymeans of puncturing the half rate convolutional code. The basic idea behind puncturingis not to transmit some of the bits output by the standard convolutional encoder, thusincreasing the rate of the code. For example, increasing the 1/2 rate to 3/4 is doneby deleting two of every six bits at the output of the encoder. The bits that are nottransmitted are dened by a puncturing pattern. Figure 3.4 illustrates the puncturingpatterns for obtaining the 2/3 and 3/4 rate convolutional code. Before the puncturedcode can be decoded, the receiver has to insert dummy zero bits into the location thatwere punctured in the transmitter.

The maximum likelihood Viterbi algorithm is used to decode the received data. Thisalgorithm can be implemented with either hard or soft decision demapping module(see section 3.1.2). Nevertheless, the soft decision is recommended method to use withViterbi decoding because it provides better performance compared to that of the harddecision, and this gain in performance does not cost any communications resources [9].

Interleaving / deinterleaving modules

In a frequency selective fading channel, the OFDM subcarriers generally have dierentamplitudes. However, the deep fades in the frequency spectrum may cause groups ofsubcarriers to be less reliable than others, thereby causing bit errors to occur in burstsrather than being randomly scattered. Most of FEC codes are not designed to dealwith error bursts. As a result, interleaving is usually employed to randomize the burstychannel errors, so that the FEC codes could be more eective.

According to the IEEE 802.11a specications, all encoded data bits shall be interleavedby a block interleaver with a block size corresponding to the number of bits in a singleOFDM symbol (NCBPS). The interleaver is dened by a two-step permutation: the rstpermutation ensures that adjacent coded bits are mapped onto nonadjacent subcarriers;the second ensures that adjacent coded bits are mapped alternately onto less and moresignicant bits of the constellation and, thereby, the probability to have contiguousstream of error bits is decreased [2].

If we denote by k the index of the coded bit before the rst permutation, i and j are theindexes of the rst and the second permutation, respectively, then the rst permutationis dened by the following rule:

i =NCBPS ∗mod(k, 16)

16+ floor(

k

16) k = 0, 1, . . . , NCBPS − 1 (3.2)


where mod(x, y) denotes modulus after division of x and y, and floor(.) denotes thelargest integer not exceeding the parameter. The second permutation is dened by therule:

j = s∗floor(i

s)+mod(i+NCBPS−floor(

16 ∗ i

NCBPS

), s) i = 0, 1, . . . , NCBPS−1 (3.3)

where s is determined by the number of coded bits per subcarrier, NBPSC , according to:

s = max(NBPSC

2, 1) (3.4)

where max(x, y) denotes the maximum value between two values, x and y.The deinterleaver, which performs the inverse operation, is also dened by two per-mutations. Here we denote by j the index of the original received bit before the rstpermutation, i is the index after the rst and before the second permutation, and k isthe index after the second permutation, just prior to delivering the coded bits to theViterbi decoder. The rst deinterleaving permutation is dened by the rule:

i = s ∗ floor(j

s) + mod(j + floor(

16 ∗ j

NCBPS

), s) j = 0, 1, . . . , NCBPS − 1 (3.5)

This permutation is inverse of the permutation described in Equation 3.3. The secondpermutation is dened as:

k = 16 ∗ i− (NCBPS − 1) ∗ floor(16 ∗ i

NCBPS

) i = 0, 1, . . . , NCBPS − 1 (3.6)

This block interleaving/deinterleaving mechanism is simple to implement using the ran-dom access memory (RAM). It is also fast and therefore introduces minimum delay inthe transmission link.

Modulation mapping / demapping modules

Pursuant to the IEEE 802.11a, the OFDM subcarriers can be modulated by one of fourdierent modulation formats, namely BPSK, Quadrature Phase Shift Keying (QPSK),16-Quadrature Amplitude Modulation (QAM) and 64-QAM. These formats are used incombination with three coding rates to achieve data rates of 6, 9, 12, 18, 24, 36, 48 and54Mbps (See Table 3.1).At the transmitter, the encoded and interleaved bit stream is converted into correspond-ing symbols stream via the symbol mapping module. The input bit stream is dividedinto groups of NBPSC (equal to 1, 2, 4 or 6) bits and converted into complex num-ber (I + jQ) representing the BPSK, QPSK, 16-QAM or 64-QAM constellation points.The conversion is performed according to Gray-coded constellation mapping schemes,illustrated in Figure 3.5, with the input bit, b0, being the earliest in the stream.


Figure 3.5: The constellations of BPSK, QPSK, 16-QAM and 64-QAM dened in IEEE 802.11a standard [2]


Table 3.1: Rate-dependent parameter [2]Coded Coded Data

Rate Data rate Modulation Coding rate bits per bits per bits perIndex (Mbps) (R) subcarrier OFDM OFDM

(NBPSC) symbol symbol(NCBPS) (NDBPS)

1 6 BPSK 1/2 1 48 242 9 BPSK 3/4 1 48 363 12 QPSK 1/2 2 96 484 18 QPSK 3/4 2 96 725 24 16QAM 1/2 4 192 966 36 16QAM 3/4 4 192 1447 48 64QAM 2/3 6 288 1928 54 64QAM 3/4 6 288 216

To achieve the same average power for all mappings, the output complex values, d, areformed by multiplying the resulting (I + jQ) value by a normalization factor, KMOD.

d = KMOD(I + jQ) (3.7)

For dierent modulation schemes, the values of normalization factor can be found inTable 3.2.

Table 3.2: Modulation-dependent normalization factor KMOD [2]Modulation KMOD

BPSK 1

QPSK 1/√

2

16-QAM 1/√

10

64-QAM 1/√

43

At the receiver, the job of symbol demapping module is to decide what was actuallyreceived. The decisions are divided into hard and soft decisions, depending on howmuch information about each transmitted bit is produced. A hard decision demappingmodule makes a denite determination of whether a bit 0 or 1 was transmitted, thusthe output of the demapping module are 0s and 1s. On the other hand, the softdecision demapping module outputs 'soft' bits, i.e. it provides the information aboutthe reliability of its decision in addition to a bit 0 or 1. This additional informationcan greatly improve the performance of the Viterbi decoder [9].


IFFT / FFT modules

The OFDM modulation is performed by Inverse Fast Fourier Transform (IFFT) algo-rithm (see Appendix C for more information). In Figure 3.2, the output of symbolmapping module is divided into NSD parallel streams by the means of the Serial to Par-allel (S/P) converter, and transformed into time-domain by IFFT module. The Parallelto Serial (P/S) converter combines the parallel signals into OFDM symbols.

Table 3.3: Timing-related parameters in IEEE 802.11a PHY layer [2]Parameter Description ValueNSD Number of data subcarriers 48NSP Number of pilot subcarriers 4NST Number of subcarriers, total 52 (NSD + NSP )∆F Subcarrier frequency spacing 0.3125MHz (=20MHz/64)TFFT IFFT/FFT period 3.2µs (1/∆F )TPREAMBLE PLCP preamble duration 16µs (TSHORT + TLONG)TSIGNAL Duration of the SIGNAL BPSK OFDM symbol 4.0µs (TGI + TFFT )TGI GI duration 0.8µs (TFFT /4)TGI2 Training symbol GI duration 1.6µs (TFFT /2)TSY M Symbol interval 4µs (TGI + TFFT )TSHORT Short training sequence duration 8µs (10 ∗ TFFT /4)TLONG Long training sequence duration 8µs (TGI2 + 2 ∗ TFFT )

Table 3.3 lists all timing-related parameters of the IEEE 802.11a. The total numberof subcarriers in one OFDM symbol is 52, in which 48 subcarriers are for transmittingdata, and other 4 are used for pilot signals. These subcarriers are numbered from -26to 26, and the 0th subcarrier, which is falling at Direct Current (DC), is not used toavoid diculties in Digital to Analog (D/A) and Analog to Digital (A/D) converterosets and carrier feedthrough in the RF system. The pilot subcarriers are put insubcarriers -21, -7, 7 and 21 of each OFDM symbol, aimed at making the coherentdetection robust against frequency osets and phase noise. The subcarrier frequencyspacing is 0.3125MHz, which makes the IFFT duration 3.2µs.At the receiver, the Fast Fourier Transform (FFT) algorithm is applied to reverse thetransmitter operation and obtain the transmitted symbol stream, which is delivered tosymbol demapping module to recover the binary data.

Guard Interval insertion and windowing

To protect the OFDM symbol from ISI and Inter-Channel Interference (ICI) and toreduce the transmitted spectrum, the Guard Interval (GI) insertion and windowing


operations are performed after IFFT (Refer to Appendix C for more information). InIEEE 802.11a, the guard interval is 800ns long, which can accommodate root meansquare (rms) delay spread up to 250ns [24]. At the receiver, the GI removal module willremove the guard period prior to FFT operation.

IQ modulator / demodulator

The main task of the IQ modulator is to modulate the complex-value OFDM sym-bols onto carrier frequency at 5GHz range before broadcasted into the channel. Atthe receiver, the IQ demodulator is used to down-convert the OFDM symbols back tobaseband for further decoding.

3.2 Description of IEEE 802.11 MAC layer

The IEEE 802.11 standard species a common MAC layer, which supports the seamlessoperation between higher layer, e.g. Logical Link Control (LLC) layer, and dierentWLAN PHY layers, such as 802.11a OFDM-based PHY. Often referred to as the brainof the WLAN, 802.11 MAC layer provides the following primary functions:

• Scanning: Before transmitting data, a WLAN STA must at least know if thereis any AP (or other STAs, in ad-hoc mode) around whom it can talk to. Scanningfunction is to enable the STA search for all APs (or STAs) in its neighbourhood.

• Authentication: This is the process of proving identity, to make sure that a STAis authorized to access the services provided by an AP (or other STAs).

• Association: Once authenticated, the STA must associate with the AP (or otherSTAs) before sending any data frame. Association is necessary to synchronize themobile STA and AP with important information, such as supported data rates.

• Privacy: This function is used to prevent the content of data frames from beingread by other than the intended recipients. The IEEE 802.11 standard providesthe optional WEP as encryption method to protect the information from eaves-droppers.

• Control of Medium Access: Since more than one STAs can share the medium(i.e. the wireless channel), the MAC layer is responsible for setting rules for theorderly access to the medium.

3.2 Description of IEEE 802.11 MAC layer 35

• Fragmentation: The optional fragmentation function enables 802.11 STA todivide a large data packet into smaller frames to transmit. Smaller frames meansmaller probability of bit errors, and thus higher chance that the receiver willreceive these frames correctly. Besides, fragmentation is done to avoid having toretransmit the whole large packet in the presence of RF interference.

• Synchronization: Timing dierence between STAs can cause collisions in WLANeven though each node is following the access protocol. Thus, it is necessary for aSTA to keep its timing as close to the timing of AP (or other STAs) as possible.This is supported by the timing synchronization function in MAC layer.

• Power Management: The optional power save mode allows a STA to turn operiodically when there is no need to send data. This function aims at conservingbattery power of the mobile STA.

Interested readers can nd the complete reference for the IEEE 802.11 standard in [3].In this section, we are going to discuss only features of the MAC layer that are necessaryfor our project.

3.2.1 802.11 MAC framing formats

The IEEE 802.11 species various frame types needed for operation of the MAC protocol.However, there are only four types of frame that are relevant to our project, namely data,Acknowledgement (ACK), Request-To-Send (RTS) and Clear-To-Send (CTS) frames.The formats of these frames are discussed briey here.

Data frame

Figure 3.6 shows the format of a data frame. It consists of the following elds:

• MAC header A data frame begins with MAC header, which comprises framecontrol, duration, addresses, and sequence control information. The MAC headerhas xed size of 30 bytes.

• Frame body This is the payload of the data frame, which has variable length,from 0 to 2312 bytes.

• FCS The Frame Check Sequence (FCS) eld is 4bytes in length, which is used toprovide integrity checking on the data frame. It contains the result of applyingthe CCITT CRC-32 polynomial to the MAC header and frame body [3].


ACK, CTS and RTS frames

The formats of ACK, RTS and CTS are dened as in Figure 3.6. The ACK frame isused to acknowledge that the data frame was received successfully. It contains only aMAC header and a FCS, and its total length is 14 bytes.The RTS frame is used to make a transmission request from the source STA to thedestination STA. It comprises of a MAC header and a FCS, with total length of 20bytes. If the destination STA is ready to receive data, it will response by a CTS frame.The format of the CTS frame is essentially the same as the ACK frame. We will discussthe RTS/CTS mechanism in details later.

Figure 3.6: The MAC frame formats [3]: (a) Data frame, (b) ACK and CTS frame, and (c) RTS frame

3.2.2 Distributed Coordination Function

The IEEE 802.11 MAC species two dierent medium access control mechanismsbetween compatible STAs: The contention-based Distributed Coordination Function(DCF) and the optional polling-based Point Coordination Function (PCF). The PCFis built on top of the DCF (as shown in Figure 3.7), and is used only on infrastructurenetworks. At present, only mandatory DCF is implemented in the 802.11-compliantproducts. In this project, the DCF is the main subject under study.The DCF achieves automatic medium sharing between STAs through the usage of Car-rier Sense Multiple Access / Collision Avoidance (CSMA/CA). Before a STA startstransmission, it senses the wireless medium for some period of time to determine ifany other STA is transmitting. If medium appears to be idle during the period, the


Figure 3.7: MAC architecture [3]

transmission may proceed, else the STA has to defer until the end of the in-progresstransmission. After deferral, or prior to attempting to transmit again immediately aftera successful transmission, the STA must select a random backo interval and wait untilthe backo clock reaches zero before transmitting. The transmission can start only ifthe medium is still idle at the end of backo interval. The CSMA/CA is both equi-table and suitable for a wireless network where collision detection is not feasible [9]. Inthe following sections, we are going to explain those techniques employed in the 802.11CSMA/CA mechanism in detail.

Carrier sensing mechanisms

The DCF regulates that an 802.11 STA must perform both physical and virtual carriersensing mechanisms. The physical mechanism is to listen to the medium and to detecta carrier (i.e. transmission activity) on the medium. The virtual mechanism is based onthe Network Allocation Vector (NAV), which always has the latest information possibleon scheduled transmission on the medium. The NAV acts as a backup mechanismto avoid collision. If a carrier is not sensed by physical means (for example, due toshadowing eects), the NAV can hopefully provide correct information on the mediumactivities. Thus, the STA should not attempt to transmit data until both physical andvirtual carrier sense mechanisms concur on the medium being idle. More informationabout setting/resetting the NAV will be presented later in section about the RTS/CTSaccess method.

Inter-Frame Spacing

The CSMA/CA mechanism requires a specied gap between contiguous frame transmis-sions. The gap between frames is called Inter-Frame Spacing (IFS). A STA must ensurethat the medium has been idle for the specied IFS before attempting to transmit. TheIEEE 802.11 denes four IFSs to provide dierent priorities for access to the wirelessmedium. They are listed here in the order from the shortest to the longest one:


EIFS

PIFS

DIFS

NEXT FRAMESIFS

LAST FRAME

Figure 3.8: The IEEE 802.11 Inter-Frame Spacings

• Short Inter-Frame Spacing (SIFS) This is the shortest of the IFSs. It is usedwhen two STAs have seized the medium and need to keep it for the duration of theframe exchange sequence to be performed. Using the smallest gap between theirtransmission, these STAs can prevent other STAs, which are required to wait forthe medium to be idle for a longer gap, from attempting to use the medium, thusgiving the priority to completion of the frame exchange sequence in progress. Forexample, the SIFS is used between a data frame and the corresponding ACK.

• PCF Inter-Frame Spacing (PIFS) This IFS is used only in STAs operatingunder the PCF to gain priority access to the medium. A STA using the PCF isallowed to transmit contention-free trac after its carrier sense mechanism deter-mining that the medium is idle for a PIFS.

• DCF Inter-Frame Spacing (DIFS) The DIFS is used by STAs operating underthe DCF to transmit data frames. The STA under DCF is allowed to transmitafter its carrier-sense mechanisms determining that the medium is idle for a DIFSplus additional backo time after a correctly received frame. If an incorrect frameis received, the EIFS is used instead of DIFS.

• Extended Inter-Frame Spacing (EIFS) This IFS is used by STAs operatingunder DCF whenever the PHY layer indicates to the MAC layer that a frametransmission was begun but did not result in the correct reception of a completeMAC frame with correct FCS value. The EIFS is dened to provide enough timefor another STA to acknowledge what was, to this STA, an incorrectly receivedframe before this STA commences transmission. The Figure 3.8 shows that ifthe last frame is not correctly received, the STA has to wait for an EIFS, plusadditional backo time, before sending the next frame.

Backo procedure

The backo interval in the DCF is often referred to as collision avoidance mechanism,which aims at reducing the collision probability between multiple STAs accessing themedium. The highest probability of collision exists when the medium becomes idle


following a busy condition. That happens because multiple STAs could have beenwaiting for the medium to become available again to transmit. Having a random backointerval for each STA could prevent multiple STAs from accessing the STA at the sametime. Additional method to further minimise collisions is to use RTS/CTS access mode,which is discussed later in this section. The backo mechanism is invoked for a STA

Figure 3.9: The random backo mechanism

in two cases: (a) When the STA attempts to transmit but nding the medium busyas indicated by either the physical or virtual carrier-sense mechanisms; and (b) Afternishing transmission of a frame (which can be either successful or failed).An example of backo time mechanism is illustrated in Figure 3.9. To begin the backoprocedure, a STA sets its backo timer to a random backo time using the followingequation:

BackoffT ime = Random() ∗ aSlotT ime (3.8)where Random() is a pseudo-random integer drawn from a uniform distribution over theinterval [0, CW ]. The CW is referred to as contention window, and it is an integer withinthe range of aCWmin and aCWmax. aSlotT ime is the slot-time value depending onthe characteristics of the PHY layer.If the medium is found to be inactive for a DCF Inter-Frame Spacing (DIFS) or Ex-tended Inter-Frame Spacing (EIFS), as appropriate, the STA starts to decrease its back-o timer. The carrier-sense mechanism is used to determine whether there is channelactivity during each backo slot. If no medium activity is indicated for the durationof a particular backo slot, then the backo procedure shall decrement its backo timeby aSlotT ime. The count-down is suspended if activity is detected on the medium, i.e.the backo timer shall not decrement for that slot. In this case, the STA must waituntil the channel is determined to be idle for a DIFS period or EIFS, before resumingits backo procedure. Only when the backo timer reaches zero, the STA can start itstransmission.


Figure 3.10: The exponential increase of contention window

The backo procedure is dictated by a binary exponential backo algorithm, which aimsat reducing the collision probability. In this algorithm, if the last attempt to transmitfails, the STA will assume that a collision has happened due to too many STAs accessingthe medium at the same time. The STA will double its contention window, CW , toavoid collision in the next transmission. Figure 3.10 illustrates the binary exponentialbacko mechanism: The initial attempt always takes CW equal to aCWmin to transmitthe packet. Then, the CW shall take the next value in the series every time there is anunsuccessful attempt to transmit that frame, until it reaches the value of aCWmax [3].The STA resets its CW to aCWmin when it receives the acknowledgement for thetransmitted data frame. For the IEEE 802.11a PHY layer, the CW value is given asfollows:

CW = 2k − 1 4 ≤ k ≤ 10 (3.9)

Table 3.4 shows important timing-related parameters for IEEE 802.11a MAC layer. Inthis table, the ACKtime is the time required to send an ACK frame at the lowestmandatory rate (i.e. 6Mbps). The aAirPropagationT ime is the anticipated time ittakes a transmitted signal to go from the transmitting STA to the receiving STA. Inaddition, the aMACProcessingT ime is the nominal time that the MAC uses to processa frame and prepare a response to the frame [3].

Basic access method

In the IEEE 802.11 standard, the DCF provides two dierent access mechanisms: Basicaccess method and RTS/CTS access method.In the basic access mode, a source STA starts to transmit the data frame directlyafter a DIFS or EIFS plus an additional backo time (as shown in Figure 3.11). Upon


Table 3.4: Timing-related parameters in IEEE 802.11a MAC layerParameter ValueaSlotT ime 9µs

aAirPropagationT ime << 1µsaMACProcessingT ime < 2µs

ACKtime 76µsSIFS 16µsPIFS 25µs (SIFS + aSlotT ime)DIFS 34µs (SIFS + 2 ∗ aSlotT ime)EIFS 126µs (SIFS + ACKtime + DIFS)

aCWmin 15aCWmax 1023

successfully decoding the data frame, the destination STA replies with an ACK toacknowledge that the data frame has been received correctly. The Short Inter-FrameSpacing (SIFS) is the time interval between reception of data frame and transmissionof the corresponding ACK frame. If the data frame is not received correctly by thedestination, no ACK frame is transmitted to the source, and the source will have toretransmit the data frame after an ACK timeout.

Figure 3.11: The Basic Access Method

The basic access mode is simple to implement and requires minimum overhead informa-tion for each data frame transmission. This provides good performance in the case ofno or very few collisions happening in the network. However, if the collisions are morelikely to happen, the performance of basic access mode is quickly degraded, due to thefact that collided data frames must be retransmitted.


RTS/CTS access method

The second access mechanism specied in DCF, the RTS/CTS access method, aims atreducing the collision probability and the impact of collision on system performance.Figure 3.12 illustrates the procedure of RTS/CTS access mechanism: before sendingthe data frame, the source STA starts by launching an RTS frame to the destination.The size of RTS frame is often much smaller than that of the data frame, and thereforeless time is required if it needs to be retransmitted due to collision or channel error.Upon successfully receiving the RTS frame, the destination STA shall reply with a CTSframe to announce that it is ready for receiving the data frame, provided that its NAVshows that the medium is idle. In other words, if the virtual carrier-sensing mechanismat the destination STA indicates the medium is not idle, that STA shall not respond tothe RTS frame. Only after the completion of exchanging RTS and CTS frame sequence,the data frame and its corresponding ACK are carried out. As a result, this method issometimes referred to as handshaking access method.

Figure 3.12: The RTS/CTS Access Mode

In combination with the virtual carrier sensing mechanism, the RTS/CTS access schemeis particularly eective against hidden terminal problem. Hidden terminal problem hap-pens when two or more STAs want to talk to the third STA, but both senders are notin the range of the other. For example, in Figure 3.13, the STA A is sending data toSTA B, and STA C is the hidden with respect to STA A. Because C is out-of-range,it could not sense the transmission from A, and therefore it could start transmitting itsowned data to B and would cause collision at B.The hidden terminal problem can be avoided, if the STAs in the above example canexchange information about how long the channel is reserved for transmission betweenany two STAs. This is done in the virtual carrier sensing mechanism of IEEE 802.11standard: A sets the duration eld in the RTS frame to B equal to the time neededto send the CTS, data, ACK frames plus three SIFS in micro-second. Likewise, B setsthe duration eld in the replied CTS frame equal to the duration eld of received RTS

3.3 Summaries 43

frame, minus one SIFS and CTS frame duration. Any STA, which is not the source ordestination, shall update its NAV according to the duration eld contained in the mostrecent and valid RTS or CTS. Then, these STAs start to count-down their NAV, and donot transmit until the NAV is counted to be zero. As a result, C, which can listen to theCTS frame from B, will defer its transmission until A and B nish their conversation(see Figure 3.13).

Figure 3.13: Hidden terminal problem and RTS/CTS access method

In the above-mentioned example, it is possible that the A does not receive the CTSframe from B due to channel impairment, and therefore it does not continue to sendthe data frame to B. In this case, C might have to wait a long time before being ableto transmit again, while the channel has become idle. To avoid such an inecient usageof medium, the IEEE 802.11 standard permits STA to reset its NAV if the channel isidle for a duration of:

NAV timeout = 2 ∗ SIFS + CTStime + 2 ∗ aSlotT ime (3.10)The CTStime is calculated using the length of CTS frame and the data rate at whichthe RTS frame used for the most recent NAV update was received [3].The disadvantage of RTS/CTS mechanism is the considerable overhead informationrequired in each transmission. Therefore, it is inecient to use this access scheme forrelatively short data frames. In IEEE 802.11, the use of RTS/CTS mechanism dependson the dot11RTSThreshold attribute. This attribute may be set on a per-STA basis,which allows STAs to be congured to use RTS/CTS either always, never or only onframes longer than a specied length.

3.3 Summaries

This chapter provides the overview of the PHY and MAC layers of the IEEE 802.11specications, which is necessary in the next sections of the report.


The IEEE 802.11a PHY layer denes the mechanism for high-speed data transmis-sion through wireless medium. With combination of dierent modulation schemes andpunctured convolutional codes, the PHY provides eight dierent data rates, from 6 to54Mbps. This opens the possibility for using link adaptation techniques.The IEEE 802.11 species a common MAC layer, which connects dierent WLAN PHYlayers to higher layer. The MAC layer provides various functions, but the most impor-tant one is to control the medium access for two or more WLAN STAs. The mandatorymedium access control mechanism is DCF, which achieves automatic medium shar-ing between STAs through the usage of CSMA/CA. It provides two dierent accessschemes, namely basic access method and RTS/CTS access method. The RTS/CTSaccess method requires more overhead information than that of basic access method,but it can help to minimise the impact of collisions and to reduce the number of collisiondue to hidden terminals.

Chapter

4Implementation and result analysis

4.1 The implementation of IEEE 802.11a simulator

In this project, we have developed a Matlab simulator to analyse the performance ofIEEE 802.11a standard under realistic multi-path channel models. The simulator canbe divided into two separate components, namely the PHY layer and the MAC layersimulator.

4.1.1 The PHY layer simulator

The PHY layer simulator aims at providing the performance of the OFDM-based 802.11aPHY layer under practical frequency-selective fading environment. Based on this infor-mation, the MAC simulator, which we will discuss in the next section, is able to decideif a packet is corrupted by channel impairment or not.Figure 4.1 is the block diagram of our PHY simulator. First, the random generator isused to create a binary sequence with specic length (e.g. 1000 bytes) in Non-ReturnZero (NRZ) format, which serves as one input data packet for the system. This datapacket is encoded by passing through the convolutional coding module. The 1/2 rateconvolutional coder is identical to that of the IEEE 802.11a standard, which we havedescribed in section 3.1.2. The convolutional coding module is equipped with puncturingcapability to create 2/3 or 3/4 rate codes. The output of the convolutional coder isinterleaved, using the block-interleaving scheme dened by the IEEE 802.11a standard.The encoded and interleaved binary sequence is then mapped onto either BPSK, QPSK,16-QAM or 64-QAM symbols, depending on the targeted data rate. The outputedsymbol stream is converted into NSD parallel streams by the S/P converter, where NSD

is the number of data subcarriers per OFDM symbol. Finally, the IFFT operation isapplied onto the parallel symbol streams for completing the OFDM modulation process.The wideband channel and AWGN channel module represents the eects of wirelesschannel on the performance of the IEEE 802.11a link. The wideband channel moduleintroduces the channel fading, while the AWGN channel module adds the additive whiteGaussian noise to the transmitted signal.

45

46 Implementation and result analysis

Figure 4.1: The block diagram of PHY layer simulator

At the receiver, the time-domain received signal is again converted to NSD parallelstreams before coming into the FFT module. The FFT operation is employed to invertthe signal back to symbol streams. The symbol streams are combined into single streamby the P/S converter. The symbol demapping and deinterleaving modules perform theinverse operations of the symbol mapping and interleaving modules at the transmitter,and return the binary stream to the Viterbi decoder. In our simulator, a hard-decisionViterbi algorithm is used to decode the received binary data.The number of both uncoded and coded bit errors are recorded during simulation atuncoded bit error counter and coded bit error counter modules. Only when the numberof uncoded (or coded) bit errors is zero, the uncoded (or coded) packet is consideredto be received successfully at the receiver. The above-mentioned processes are repeatedfor number of times, which is referred to as the number of packets sent in simulation,Npackets. As a result, we are able to calculate both of Bit Error Rate (BER) andPacket Error Rate (PER), with and without convolutional coding in our simulation.In the PHY layer simulator, we follow few assumptions to simplify the simulation. First,we assume that the binary sequence outputed from the random generator has equalprobabilities of -1 and 1, and there is no long run of either -1 or 1. Thus, thescrambler and descrambler required in IEEE 802.11a can be omitted in our simulation.Secondly, we assume that the timing and frequency are perfectly synchronised betweenthe transmitting and receiving STA, and there is no degradation in system performance

4.1 The implementation of IEEE 802.11a simulator 47

due to timing error, frequency oset or phase noise. This is an optimistic assumption,because these problems often severely bring down the performance of OFDM-basedsystem, unless proper synchronization techniques are employed. Thirdly, we assume thatthe channel estimation at the receiver is perfectly done, i.e. the receiver has completeinformation of the channel impulse response at each data subcarrier, in both amplitudeand phase. As a result, the receiver is able to compensate for channel fading and phasechange at each data subcarrier. Again, this assumption is idealistic because perfectchannel estimation can never be achieved in practice.

4.1.2 The MAC layer simulator

The MAC layer simulator is the one of the main objects in our project. It aims atproviding an accurate measure of the IEEE 802.11 MAC performance, based on PHYsimulator information. The MAC simulator is an event-based simulation, and its op-eration can be best described by the state-machine diagrams in Figure 4.2, 4.3, and4.4.

UPDATENAV

RESPONSEWITH CTS

TRANSMITTINGDATA

RESPONSEWITH ACK

− Frame received correctly− It is not for the receiving STA

− Channel free &

− CTS received successfully

− Channel free &

− The frame cannot be decoded or

the ACK isreceived successfully

− Channel free &

− RTS received successfully

− Channel free &

− DATA received successfully− Channel free &

RECEIVING

Channel busy

SENSING

Figure 4.2: The state-machine diagram for an IEEE 802.11a station in passive mode

Figure 4.2 shows the state-machine diagram for an IEEE 802.11a STA in passive mode.The passive mode is dened as when the STA is sensing the medium or receiving packets


WAIT FOR ACK

Channelfree

ACK received successfully

to transmitand no other packets

The channelis still free after

a wait period

The channel becomesbusy during a wait period

ACK received successfully andthere is another packet

to transmit

ACK timeout or

transmittingFinish

WAIT TO TRANSMIT

TRANSMIT DATA

READY

IDLEPacket arrives

Figure 4.3: The state-machine diagram for an IEEE 802.11a station in active mode (basic access mode)

after a wait−periodis still freeThe channel

Channelfree

during a wait−period

The channelbecomes busy

correctlyCTS received

packet to transmitACK received and no other

there is other packet to transmitACK timeout or ACK received but

Packetarrives

timeoutCTS

WAIT TOTRANSMIT

Finishtransmitting

TRANSMIT RTS

READY

IDLE

WAIT FOR CTS

TRANSMIT DATA

Finish transmitting

WAIT FOR ACK

Figure 4.4: The state-machine diagram for an IEEE 802.11a station in active mode (RTS/CTS access mode)


from other STAs through the medium. The default state of the STA in passive modeis Sensing. If a channel-busy event is received, which indicates that another STA hasjust started to transmit, this STA shall change to Receiving state. The Receiving stateends when the channel-free event, indicating the end of the transmission, is recorded.Depending on additional information, such as the correct or incorrect decoding of thereceived frame, type of the received frame, and destination address on that frame, theSTA shall respond dierently. For example, if the frame is received correctly, but thedestination address is not corresponding to this STA's address, it shall update its NAVand return to Sensing state. This state-machine diagram can be used for both basicaccess mode and handshaking (i.e. RTS/CTS) access mode.Similarly, the Figure 4.3 and 4.4 describe operations of the STA in active mode, for basicand handshaking access methods, respectively. The active mode is dened as when theSTA attempts to transmit data packet. Since these two state-machine diagrams aresimilar, we need to explain only the diagram for basic access mode. The Idle stateis the default state of the STA in active mode. If a packet-arrive event is indicated,the STA shall change its state to Ready. At this state, after a channel-free event isgenerated (either by this STA or other neighbouring STAs), the STA moves to Wait−To−Transmit state. It is required that the STA stay in this state for a duration equal toDIFS plus an additional random backo time, before attempting to transmit data packet.If the channel turns into busy during wait period, the STA has to return to Ready state.After transmitting the data frame, the STA changes to Wait − For − ACK state. Itwaits here for a duration equal to ACK timeout, to decide if the transmitted packethas been successfully received or not. If an ACK frame is received successfully duringtimeout period, the STA can change to either Idle (if no more packet to transmit) orReady state (if there is packet to transmit in queue). Otherwise, the STA has to returnto Ready state to perform re-transmission of data frame.

4.1.3 Choice of simulation parameters

In this project, the PHY and MAC simulations adopt all standard parameters from theIEEE 802.11a specications, which are mentioned in Table 3.1, 3.2, 3.3 and 3.4.In addition, Table 4.1 lists all other parameters used in our PHY and MAC layer sim-ulations. The carrier frequency, fc, is chosen to be 5GHz, which approximates thefrequency of 802.11a WLAN devices. Although the output power of IEEE 802.11a STAcan vary and be as high as 800mW [2], we choose one constant transmitted power, PTX ,of 50mW (or 17dBm) for all STAs during simulation. It is equal to the maximum allow-able transmitting power for WLAN devices at 5GHz band regulated by the Danish radiointerface specication [7]. We select the noise oor to be -93dBm, which is the samevalue used in [20]. The path-loss exponent, n, is chosen to be 3.5, which represents thepath-loss characteristic in oce building [21]. Since the throughput of WLAN devices is


insignicant in region where the SNR of received signal is low, we assume that a packetis always discarded if the SNR is less than SNRmin. As a result, the usable range ofreceived power is from -83 to 17dBm.

Table 4.1: Parameters for PHY and MAC layer simulationsDescription Notation Value

Carrier frequency fc 5GHzTransmitting power PTX 17dBmLevel of noise oor PNOISE -93dBmMinimum SNR level SNRmin 10dB

Usable range of received power PRX -83 to 17dBmPath-loss exponent n 3.5

Type of channel models Env A, B, C, D and E

Doppler spread BD 5HzSize of PSDU Pksize 1000bytesACK timeout ACKtimeout 108µs (2 ∗ SIFS + ACKtime)CTS timeout CTStimeout 108µs (2 ∗ SIFS + ACKtime)Detection time Tdet 4µs

Practical wireless channels are measured in [12], and equivalent channel models aredeveloped for the HIPERLAN/2 simulation in [13]. These channel models, referred toas environments A, B, C, D and E, represent realistic scenarios for simulation. Sincethe spectrum of HIPERLAN/2 is almost identical to that of the IEEE 802.11a, we canapply these channel models in our simulation. Table 4.2 provides brief description foreach environment, and their PDPs are illustrated in Figure 4.5. For completeness, thedetailed characteristics of these environments are given in Appendix D.

Table 4.2: Channel models for PHY layer simulationEnvironment Description

A Typical oce environment for No Line Of Sight (NLOS) con-dition with 50ns rms delay spread.

B Typical large open space and oce environment for NLOScondition and 100ns rms delay spread.

C Typical large open space environment for NLOS condition,and 150ns rms delay spread.

D The same as environment C, but for LOS condition. A 10dBspike at zero excess delay has been added resulting in a rmsdelay of about 140ns.

E Typical large open space environment for NLOS condition,and 250ns rms delay spread.


0 200 400 600 800 1000 1200 1400 1600−35

−30

−25

−20

−15

−10

−5

0The PDP of various environments

Delay (ns)

Nor

mal

ized

pow

er (

dB)

Environment AEnvironment BEnvironment CEnvironment D (first tap−Ricean)Environment E

Figure 4.5: The PDPs of various environments

In our simulation, the STAs are assumed to be stationary. However, the channel char-acteristics are changing. The Doppler spread of the channel, BD, is selected to be 5Hz,which is consistent with the measurement results in oce building [5].

The size of PSDU, which is actual information carried by a MAC frame, is 1000 bytesin our simulation. From now on, it is referred to as the packet size, Pksize. TheIEEE 802.11 mentions the ACKtimeout and CTStimeout, but does not specify theirvalues [3]. In our MAC layer simulation, we dene the ACKtimeout and CTStimeout

to be equal to the duration for transmitting an ACK frame (or CTS frame, which isidentical) at the minimum mandatory data rate, plus two SIFS. In addition, we alsospecify Tdet equal to 4µs, which is the duration for STA to detect the transmission fromanother STA. That means if a STA starts its transmission at time t, then other STAs willonly be aware of such transmission after t+Tdet. The value of Tdet is chosen to be greaterthan the air propagation delay, aAirPropagationT ime, and MAC processing time atthe receiving STA, aMACProcessingDelay, specied in the IEEE 802.11a standard [2].

4.1.4 Simulation scenarios

The performance of MAC layer is analysed under two dierent simulation scenarios (seeFigure 4.6). It is explained in the following sections.


Scenario I

In this scenario, there are two STAs located at distance d from each other. The tracmodel for this scenario is balanced and fully loaded. It means that the oered load ismuch higher than the maximum throughput and there is always at least one packet inthe transmission queue.

STA STA

d

Frames Frames

Frames Frames

Frames Frames

Frames

d

(b)

STA

STA

STA

STASTA

(a)

AP

Figure 4.6: (a) Simulation scenario I, and (b) Scenario II

The main purpose of this scenario is to identify the maximum goodput of MAC layer.It is important to note that, since there are only two nodes, hidden terminal problemdoes not happen in this scenario.

Scenario II

The second scenario consists of one AP and ve STAs. The AP is located at the centreof the circle with radius d, while ve STAs are distributed uniformly on the circle. Forthis scenario, it is possible to have hidden terminal problem when the radius d becomeslarge. All the STAs generate the same trac load of 1Mbps and the packet inter-arrivaltime is exponentially distributed. There is no trac generated at the AP.

4.2 Analysis of simulation results 53

Time

Inter−arrival time

Holding time Idle time

Departure timeArrival time

Idle

Busy

Figure 4.7: Illustration of terminology applied for trac process[1]

The trac model, where packet inter-arrival time is represented by exponentially dis-tributed random process, is often used to describe the typical scenario of a packet-basedcommunication system. Figure 4.7 illustrates the packet inter-arrival time, which isthe time interval between two arrivals of contiguous packets. The sole parameter thatdescribes this type of trac model is the intensity of arrival, λ, which is calculated asfollows:

λ =OfferedLoad

Pksize(4.1)

where OfferedLoad is the oered trac load and Pksize is the size of packet. Inaddition, the mean packet inter-arrival time µ is inversely proportional to the intensityof arrival [18]:

µ =1

λ(4.2)

In our case, for a packet size of 1000bytes and an oered trac load of 1Mbps, the meaninter-arrival time is 8000µs. We are going to use this mean to generate the instantaneouspacket inter-arrival times for our simulation.

4.2 Analysis of simulation results

In this section, we are going to present our analyses on the results obtained from thesimulators and the set of parameters mentioned in 4.1. Our analyses are divided intothree parts: (a) performance of the IEEE 802.11a PHY, (b) performance of the standardMAC layer, and (c) performance of the proposed link adaptation schemes.

4.2.1 Performance of the IEEE 802.11a PHY layer

The benet of OFDM technique

Figure 4.8 shows the uncoded BER for BPSK modulation under various environments.The theoretical BER for BPSK modulation on both AWGN and at-fading Rayleighchannels are included for comparison.


0 5 10 15 20 25 30 35 4010

−5

10−4

10−3

10−2

10−1

Averaged symbol SNR in dB

BE

RUncoded BER for BPSK in various environments

Theoretical AWGNTheoretical Rayleighsimulated Rayleigh (1−tap)simulated Ricean (1−tap)Environment AEnvironment BEnvironment CEnvironment DEnvironment E

Figure 4.8: The uncoded BER of BPSK under various environments

As we can see from Figure 4.8, the OFDM technique eectively turns the frequency-selective fading channels into at fading ones. The BER performance of environmentA, B, C and E is identical to that of at fading Rayleigh channel. For environmentD, where a Ricean component is present, the BER at a given SNR is slightly lower.However, due to the existence of the other taps, the result does not completely coincidewith that in a purely Ricean channel.

The in uences of environments

It is necessary to understand the inuences of dierent channel models on both ofthe uncoded and coded PER performance of IEEE 802.11a PHY layer. Figure 4.9represents the uncoded PER performance of BPSK modulation scheme under variousenvironments, while Figure 4.10 and 4.11 show the coded PERs for data rate number 1and 8, respectively. The packet size in this simulation is 1000 bytes.Figure 4.9 shows two interesting points. First, at the low SNR region, the uncoded PERperformance of a Rayleigh fading channel is better than that of a Ricean fading channel.In a Rayleigh fading channel, the bit errors are not evenly distributed between packets.Some packets, which experience deep fades, receive more bit errors than the others, andsome packets, which experience channel gain, can have little or no bit errors at all. Onthe other hand, the Ricean fading channel is close to an AWGN, which is a Binary


0 5 10 15 20 25 30 35 4010

−2

10−1

100


PE

R

Uncoded PER for BPSK under various environments (Pksize = 1000 bytes)

Environment AEnvironment BEnvironment CEnvironment DEnvironment ERayleigh flat fadingRicean flat fading

Figure 4.9: The uncoded PER for BPSK under various environments

0 5 10 15 20 25 30 35 40

10−2

10−1

100


PE

R

Convolutional coded PER under various environments (Pksize = 1000 bytes, Rate Index = 1)


Figure 4.10: The convolutional coded PER under various environments (Rate Index = 1)


0 5 10 15 20 25 30 35 4010

−1

100


PE

RConvolutional coded PER under various environments (Pksize = 1000 bytes, Rate Index = 8)


Figure 4.11: The convolutional coded PER under various environments (Rate Index = 8)

Symmetric Channel (BSC) with uniformly-distributed bit error pattern. This results ina poorer PER performance at low SNR region compared to the Rayleigh fading channel.Secondly, among the wideband environments, the environment A provides somewhatbetter PER performance than that in other environments at low SNR region. Thisis due to the fact that environment A has the smallest rms delay spread. A smallerdelay spread is equivalent to a smaller ratio of OFDM signal bandwidth and channelcoherence bandwidth. In such a situation, the channel frequency response is relativelyat within the OFDM signal bandwidth, or all OFDM subcarriers experience a similarfading level [24]. If the channel changes slowly during packet duration, bit errors tend toconcentrate on some packets, which leaves some other packet error-free or having verylittle bit errors. On the other hand, in other environments when there is a larger rmsdelay spread, only a smaller number of subcarriers are aected by the fading. Therefore,the bit errors spread over packets more randomly, even if the channel is changing slowlycompare to packet duration. This results in a worse PER performance than that inenvironment A. The same reason applied to explain the fact that the Rayleigh atfading channel performs much better than the wideband channels in terms of uncodedPER, even though their uncoded BER curves are very similar.The coded PER curves in Figure 4.10 and 4.11 show the same tendencies as thoseuncoded ones. The environment A has slightly better coded PER performance thanthose of other environment at low SNR region. Since the coded PERs of environments


B, C, D and E are very similar, it is not necessary to analyse MAC layer performancefor all of them. In the next section, we will run MAC simulation only for environment A

and E. As we can see from the gures, using Rayleigh fading channel to analyse MAClayer performance is an optimistic assumption, because the practical scenario wouldgenerally perform much worse.

The eects of modulation and coding schemes

In Figure 4.12, we compare the coded PER for dierent data rates dened by the IEEE802.11a standard. The data rates are numbered from 1 to 8, which are corresponding todierent combinations of modulation and coding schemes (see Table 3.1). An uncodedPER curve using BPSK modulation is drawn in the same gure for comparison. Theenvironment for evaluation is A, and the packet size is 1000 bytes.

0 5 10 15 20 25 30 35 40

10−2

10−1

100


PE

R

Convolutional coded PER at various data rates (Environment A, Pksize = 1000 bytes)

Rate Index = 1Rate Index = 2Rate Index = 3Rate Index = 4Rate Index = 5Rate Index = 6Rate Index = 7Rate Index = 8Uncoded PER for BPSK

Figure 4.12: The convolutional coded PER for dierent data rates

First, we take a look at the dierence between the uncoded PER using BPSK modu-lation and the coded PERs at data rate number 1 and 2, which have 1/2 and 3/4 rateconvolutional coding, respectively, applied on top of the BPSK modulation. It is clearthat the convolutional coding helps reducing the system PER considerably. At highSNR value, the coding gain is up to 7dB for 1/2 rate coder, or approximately 4dB for3/4 rate coder.


In general, the PER performance is degraded when a higher data rate is used. The onlyexception is the data rate number 2. Our simulation shows that the rate number 3 canperform equally to the data rate number 2. It is also important to note that the datarate number 4 and 7 have very close performance to that of 5 and 8. The impact of suchsimilarity is going to emerge more clearly later in section 4.2.2.

The eects of packet sizes

Figure 4.13 illustrates the eects of the packet size on the coded PER performance. Theenvironment A and data rate number 1 are used for simulation. The packet sizes underevaluation are 20, 500, 1000 and 2000 bytes.

0 5 10 15 20 25 30 35 4010

−3

10−2

10−1

100


PE

R

Convolutional coded PER for different packet sizes (Environment A, Rate Index = 1)

Pksize = 20 bytesPksize = 500 bytesPksize = 1000 bytesPksize = 2000 bytes

Figure 4.13: The uncoded BER of BPSK for dierent packet sizes

Naturally, the larger the packet size, the higher the coded PER is. As we can see fromthe gure, packet size of 20 bytes can be very reliable. It means small frames, such asRTS, CTS or ACK, have greater chance of being received successfully. On the otherhand, larger packet sizes, such as 500, 1000 and 2000 bytes, are far less reliable. However,large packet size is still employed in practice. The main reason for using large packetsize is to decrease the ratio between overhead information and data within one packet.In another words, a data packet should neither be too small, which is inecient in termsof overhead information, nor too large because of the high probability of packet error.The gure indicates that the performance of 500, 1000 and 2000-byte packet sizes is


only slightly dierent from each other. Thus, we use only the packet size of 1000 bytesto evaluate the MAC layer performance in the next section.

4.2.2 Performance of the IEEE 802.11a MAC layer

The eects of data rates

Performance of the IEEE 802.11a MAC layer depends greatly on the data rate used atthe PHY layer. In Figure 4.14, we present the performance of the MAC layer, in termsof goodput, at all eight available data rates. The goodput is dened as the ratio betweentotal number of information bits received at the destination and the total time neededfor transmission. The simulation scenario I is used for evaluation, and resulted totalgoodputs are plotted against the distance d between two STAs. The total goodput isthe goodput of the whole WLAN system, which consists of two nodes in this scenario.In this simulation, the basic access scheme, environment A and packet size of 1000 bytesare employed. In addition, Figure 4.15 and 4.16 are respectively the probabilities ofpacket errors and collisions for dierent data rates, which are obtained from the samesimulation.

0 5 10 15 20 25 300

5

10

15

20

Distance (m)

Goo

dput

(M

bps)

Goodput for Basic Access Mode (Scenario I, Environment A, Pksize = 1000 bytes)

Rate Index = 1Rate Index = 2Rate Index = 3Rate Index = 4Rate Index = 5Rate Index = 6Rate Index = 7Rate Index = 8

Figure 4.14: Total goodputs for dierent data rates (basic access method, environment A)

Figure 4.14 shows clearly that low data rate, while cannot provide high goodput, isable to achieve reliable connection even at large distance. In contrast, higher data rate,


which oers higher throughput at close distance, does not work well at large distance.It is because the PER performance of higher data rate is degraded quickly with SNR,or equivalently with distance (see Figure 4.15). In practice, it is desirable that the STAis able to select an optimum data rate for its transmission, according to instantaneouslink condition.We observe that the goodputs of data rates number 2, 4 and 7 are often below that ofthe other rates. In [5], these rates are said to contribute little or nothing to increasethe throughput, if link adaptation scheme is to be implemented. However, as we aregoing to discuss later in section 4.2.3, these data rates do have some inuences on theperformance of the link adaptation.

0 5 10 15 20 25 300

10

20

30

40

50

60

70

80

90

100

Distance (m)

Pro

babi

lity

of p

acke

t err

ors

(%)

Probability of packet errors for Basic Access Mode (Scenario I, Environment A, Pksize = 1000 bytes)


Figure 4.15: The probabilities of packet errors for dierent data rates (basic access method, environment A)

It is also interesting to look at the collision probability obtained from our simulation.Figure 4.16 shows that collisions are more likely to happen at close distance than atlarge distance, and for lower data rate than for higher data rate. The reason is thatthe collision probability depends on the value of contention windows, CW , and on thenumber of STA simultaneously sharing the medium. At a close distance, or for a lowdata rate, where the probability of re-transmission due to packet error is small, theaverage CW is small. The average CW is getting larger at large distance, or for higherdata rate, due to the fact that more re-transmissions are needed due to packet errors.This resulted in the tendency of collision probability as shown in Figure 4.16.


0 5 10 15 20 25 300

1

2

3

4

5

6

7

Distance (m)

Pro

babi

lity

of c

ollis

ions

(%

)

Probability of collision for Basic Access Mode (Scenario I, Environment A, Pksize = 1000 bytes)


Figure 4.16: The probabilities of collision for dierent data rates (basic access method, environment A)

In addition, for delay-sensitive applications, such as voice or real-time video, the meantransfer delay is a more useful performance measure than the goodput. Figure 4.17illustrates the delay performance for all available data rates in IEEE 802.11a standard.The highest data rate, number 8, oers minimum delay at close range up to 10 meters.However, at distance greater than 10 meters, data rate number 1 and 3 start to providemuch lower transmission delay than that of rate 8. Again, a good link adaptation schemeshould be able to provide the minimum transfer delay corresponding to a specic linkcondition.

Basic access method vs. RTS/CTS access method

The choice of basic access method or handshaking access method does have inuence onthe performance of the MAC layer. First, we discuss the dierences between these twoaccess schemes under simulation scenario I. The total goodputs for eight dierent datarates with RTS/CTS access method are shown in Figure 4.18. To assist comparison,the goodput for data rate number 1 with basic access method is included in this gure.In addition, Figure 4.19 illustrates the mean transfer delays for dierent data rates inRTS/CTS access method.We can observe from Figure 4.18 that the goodputs of RTS/CTS access method are very


0 5 10 15 20 25 300

2

4

6

8

10

12

14

16

18

20

Distance (m)

Ave

rage

tran

sfer

del

ay (

ms)

Transfer delay for Basic Access Mode (Scenario I, Environment A, Pksize = 1000 bytes)


Figure 4.17: The mean transfer delay for dierent data rates (basic access method, environment A)

0 5 10 15 20 25 300

2

4

6

8

10

12

14

16

Distance (m)

Goo

dput

(M

bps)

Goodput for Handshaking Access Mode (Scenario I, Environment A, Pksize = 1000 bytes)

Rate Index = 1Rate Index = 2Rate Index = 3Rate Index = 4Rate Index = 5Rate Index = 6Rate Index = 7Rate Index = 8Rate Index = 1 (BA)

Figure 4.18: Total goodputs for dierent data rates (RTS/CTS access method, environment A)


0 5 10 15 20 25 300

2

4

6

8

10

12

14

16

18

20

Distance (m)

Ave

rage

tran

sfer

del

ay (

ms)

Transfer delay for Handshaking Access Mode (Scenario I, Environment A, Pksize = 1000 bytes)

Rate Index = 1Rate Index = 2Rate Index = 3Rate Index = 4Rate Index = 5Rate Index = 6Rate Index = 7Rate Index = 8Rate Index = 1 (BA)

Figure 4.19: The mean transfer delay for dierent data rates (RTS/CTS access method, environment A)

similar to those of basic access method presented in Figure 4.14. However, the RTS/CTSaccess method oers slightly lower goodput under this particular simulation scenario.This is due to the fact that additional overhead information (RTS/CTS frames) areintroduced in the handshaking access scheme. For the same reason, the mean transferdelays of RTS/CTS access method are also higher compared to those of basic accessmethod (see Figure 4.19).Secondly, the performance of the basic access and handshaking access method are ex-amined under simulation scenario II. In Figure 4.20, the resulted goodputs for data ratenumber 1 and 8 using basic access and handshaking access schemes are plotted againstthe radius d of the circle in scenario II. In this simulation, environment A and packetsize of 1000 bytes are used.At close distance, which is less than 20 meters, the basic access scheme continues to oerhigher throughput. However, the RTS/CTS access mode begins to provide much bettergoodput at distance greater than 20 meters. This is because the hidden terminal problemcan occur in scenario II at this range. Due to hidden terminal problem, the probabilityof collision for data rate number 1 using basic access scheme suddenly increases (seeFigure 4.21). On the other hand, the RTS/CTS access scheme with virtual carrier-sensing mechanism, which is designed to mitigate the hidden terminal problem, hasmuch lower probability of collision. Consequently, the handshaking access scheme can


0 5 10 15 20 25 300

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5

Distance (m)

Goo

dput

(M

bps)

Total goodput at simulation scenario II (Environment A, Pksize = 1000 bytes)

BA, Rate Index = 1HA, Rate Index = 1BA, Rate Index = 8HA, Rate Index = 8

Figure 4.20: Total goodput at simulation scenario II (Environment A)

0 5 10 15 20 25 30 350

5

10

15

20

25

30

35

40

45

Distance (m)

Pro

babi

lity

of c

ollis

ion

(%)

Probability of collision at simulation scenario II (Environment A, Pksize = 1000 bytes)

BA, Rate Index = 1HA, Rate Index = 1

Figure 4.21: Probability of collision at simulation scenario II (Environment A)


oer reasonable goodput at large distance, even if some of the STAs are hidden fromthe others.

The eects of environments on performance of the MAC layer

In this section, we study the eects of the environments on the performance of the IEEE802.11a MAC layer. Figure 4.22 is the goodput obtained from environment A and E

under simulation scenario I. The packet size is 1000 bytes.

0 5 10 15 20 25 300

5

10

15

20

Distance (m)

Goo

dput

(M

bps)

Goodput comparison between environment A and E (Scenario I, Pksize = 1000 bytes)

Rate Index = 1 (Env E, BA)Rate Index = 8 (Env E, BA)Rate Index = 1 (Env E, HA)Rate Index = 8 (Env E, HA)Rate Index = 1 (Env A, BA)Rate Index = 8 (Env A, BA)Rate Index = 1 (Env A, HA)Rate Index = 8 (Env A, HA)

Figure 4.22: Total goodputs in environment A and E

We have discussed in section 4.2.1 that the environment A has slightly better PERperformance than that of other environments. Due to this reason, the MAC layerperformance is higher in environment A for both basic access and handshaking accessmethods at large distance (see Figure 4.22). At close distance, where the SNR is highenough to consider the channel error-free, the goodputs for both environments approachthe maximum goodput of the IEEE 802.11a MAC layer.

4.2.3 Performance of link adaptation mechanism

In this section, we discuss the performance and eciency of the link adaptation mech-anism proposed in [5] under realistic channel models. The performance evaluation is


done using two dierent simulation scenarios: scenario I represents the best-case, whilescenario II depicts one typical usage scenario of WLAN system. We also discuss theeect of the data rate number 7 in the proposed link adaptation scheme.

Performance evaluation with scenario I

Figure 4.23 and 4.24 are the total goodputs of the link adaptation schemes with basicaccess and handshaking access mode, respectively. It is important to note that only datarates number 1, 3, 5, 6, 7 and 8 are used for link adaptation in this simulation scenario.The reason for using these data rates will be explained later in a separate section. Forcomparison, goodputs of xed data rates, from 1 to 8, are also displayed. However,not all supported rates are shown, because goodputs of data rate number 2, 4 and 7are often below or close to those of other rates (see section 4.2.2). The link adaptationscheme is evaluated with three dierent sets of parameters: (S = 3, F = 1), (S = 10,F = 1) and (S = 3, F = 2). The S parameter is referred to as Success Threshold: it isthe number of successful transmissions that the transmitter should achieve before it canassume that the link quality has improved and switch to a higher data rate. In contrast,the F parameter is called Failure Threshold, and if the number of failed transmissionsis equal to F , the transmitter should fall back to a lower data rate.

0 5 10 15 20 25 300

5

10

15

20

Distance (m)

Goo

dput

(M

bps)

Goodput for Link Adaptation with Basic Access Mode(Scenario I, Environment A, Pksize = 1000 bytes)

Rate Index = 1Rate Index = 3Rate Index = 5Rate Index = 6Rate Index = 8Link Adpt (S=3, F=1)Link Adpt (S=10, F=1)Link Adpt (S=3, F=2)

Figure 4.23: Total goodput of link adaptation for basic access method


0 5 10 15 20 25 300

2

4

6

8

10

12

14

16

Distance (m)

Goo

dput

(M

bps)

Goodput for Link Adaptation with Handshaking Access Mode(Scenario I, Environment A, Pksize = 1000 bytes)

Rate Index = 1Rate Index = 3Rate Index = 5Rate Index = 6Rate Index = 8Link Adpt (S=3, F=1)Link Adpt (S=10, F=1)Link Adpt (S=3, F=2)

Figure 4.24: Total goodput of link adaptation for handshaking access method

There are very similar tendencies in both of Figure 4.23 and 4.24. First, the set ofparameters (S = 10, F = 1) provides much lower goodput than the other sets at closedistance. It is due to the fact that the link adaptation scheme, with a large value ofS, cannot react fast enough to the improvement of the link quality, i.e. the STA willmaintain a low transmission rate although the quality of the link allows the use of ahigher rate [5]. However, at large distance, where only the lowest data rate is possible,S = 10 leads to a slightly better goodput performance compared to those of S = 3.The reason is that, in this case, a large value of S can avoid ineective switching tohigher rates when the channel has not improved. Large value of S is also said to beeective when the quality of the link is changing very slowly [5], for similar reason. Inour simulation, the channel changing rate is xed at 5Hz and the value of S = 3 isproved to be a better choice at this particular rate.

Secondly, we can observe the performance of dierence values of F . The set of param-eters (S = 3, F = 1) achieves the higher goodput at distance larger than 10 meters,but (S = 3, F = 2) is superior at closer distance. Ideally, the link adaptation schememust be able to distinguish whether a collision or a change of link quality is the causeof transmission failure, and it should only decrease the data rate when a change of linkquality is detected. However, such distinction is not possible. The value F = 1 dic-tates the STA to reduce its transmission rate whenever a transmission failure occurs,


0 5 10 15 20 25 300

1

2

3

4

5

6

7

Distance (m)

Pro

babi

lity

of c

ollis

ions

(%

)Probability of collision for Link Adaptation with Basic Access Mode (Scenario I, Environment A, Pksize = 1000 bytes)

Rate Index = 1Rate Index = 3Rate Index = 5Rate Index = 6Rate Index = 8Link Adpt (S=3,F=1)Link Adpt (S=10,F=1)Link Adpt (S=3,F=2)

Figure 4.25: Probability of collision of link adaptation for basic access method

regardless of the cause of failure. This scheme works well at large distance, becausemost of transmission failures are due to the channel quality. At close distance, wherethe link quality is very good, collision becomes the main source of failure (see Figure4.25). Therefore, a larger value, F = 2, is a better choice in this case, because it reducesthe probability of falling back to lower data rate incorrectly due to collision. This isvery important analysis, and we are going to use it for modication of the original linkadaptation scheme in the next section.

Figure 4.26 and 4.27 are the mean transfer delay of the link adaptation scheme usingbasic access and handshaking access method, respectively. The transfer delays of xeddata rates number 1, 3, 5, 6 and 8 are also included for comparison.

Figure 4.26 and 4.27 show that the (S = 10, F = 1) has relatively higher delay thanthe other sets of parameters at close range, but it starts to provide lower delay withincreasing of distance. In contrast, the (S = 3, F = 2) oers the smallest transfer delayat close distance, and very large delay at large distance. While the dierence in termsof goodput for the set (S = 3, F = 1) and (S = 3, F = 2) at close distance is signicant(up to 1-1.5Mbps in Figure 4.23 and 4.24), the gap between their delay curves is reallysmall. Therefore, in terms of mean transfer delay, (S = 3, F = 1) is the best choiceamong three sets of parameters for this simulation scenario.


0 5 10 15 20 25 300

2

4

6

8

10

12

14

16

18

20

Distance (m)

Ave

rage

tran

sfer

del

ay (

ms)

Transfer delay for Link Adaptation with Basic Access Mode (Scenario I, Environment A, Pksize = 1000 bytes)


Figure 4.26: Transfer delay of link adaptation for basic access method

0 5 10 15 20 25 300

2

4

6

8

10

12

14

16

18

20

Distance (m)

Ave

rage

tran

sfer

del

ay (

ms)

Transfer delay for Link Adaptation with Handshaking Access Mode(Scenario I, Environment A, Pksize = 1000 bytes)


Figure 4.27: Transfer delay of link adaptation for handshaking access method


Performance evaluation with scenario II

The simulation scenario II serves as a typical usage setting for IEEE 802.11a WLANsystem. Figure 4.28 and 4.29 shows the average goodput of all individual STAs usingthe above-mentioned link adaptation scheme (S = 3, F = 1). For comparison, themean goodputs for xed data rates number 1 and 8 are also plotted in these gures.Environment A and packet size of 1000 bytes are used for evaluation.

0 5 10 15 20 25 300

0.2

0.4

0.6

0.8

1

Distance (m)

Ave

rage

goo

dput

(M

bps)

Average goodput for basic access method at simulation scenario II(Environment A, Pksize=1000 bytes)

BA, Rate Index = 1BA, Rate Index = 8Link Adpt (S=3,F=1)

Figure 4.28: Average goodput of link adaptation for basic access method

In both Figure 4.28 and 4.29, the link adaptation outperforms the xed rate schemes.With link adaptation, the average goodput of 1 Mbps is maintained at a radius up to15 meters for all ve STAs. At larger radius, the goodput declines, but it is still higherthan that of data rate number 1.

For basic access method, the average goodput drops suddenly at large distance, dueto hidden terminal issue. In contrast, the RTS/CTS access scheme is able to sustainsignicant average goodput even at large distance, for both xed data rate and linkadaptation scheme. This observation stimulates the idea of a link adaptation schemecapable of using basic access and handshaking access method alternatively to achievebetter goodput.


0 5 10 15 20 25 300

0.2

0.4

0.6

0.8

1

Distance (m)

Ave

rage

goo

dput

(M

bps)

Average goodput for handshaking access method at simulation scenario II(Environment A, Pksize=1000 bytes)

HA, Rate Index = 1HA, Rate Index = 8Link Adpt (S=3,F=1)

Figure 4.29: Average goodput of link adaptation for handshaking access method

The eect of data rate number 7

In previous sections, data rate number 1, 3, 5, 6, 7 and 8 are always used for linkadaptation. In this section, we discuss the reason behind the selection of these datarates.As we mentioned earlier, in [5], the data rate number 2, 4 and 7 are said to contributelittle or nothing to increase the throughput of link adaptation scheme. Two link adap-tation schemes are simulated under scenario I to verify this assumption. One of themuses data rate number 1, 3, 5, 6 and 8, while the other switches between rate number 1,3, 5, 6, 7 and 8. Both of them use the set of parameters (S = 3, F = 1). The goodputsobtained from simulation are presented in Figure 4.30.We can see clearly that the goodputs for link adaptation with and without data ratenumber 7 are dierent. At close distance, the link adaptation with rate 7 generally oersbetter goodput that that of link adaptation without rate 7. This phenomenon can beexplained in the same way as we have rationalised the advantage of using parameterF = 2 at close distance. At close distance, the link quality is often good enough forusing the highest available data rate, which is number 8, for transmission; and collisionis the main source of transmission failure. If the link adaptation decreases its data rateincorrectly due to collision, descending from 8 to 7 it's obviously better than from 8 to


0 5 10 15 20 25 300

5

10

15

20

Distance (m)

Goo

dput

(M

bps)

Goodput for Link Adaptation with and without data rate 7(Environment A, Pksize = 1000 bytes)

Incl. rate 7 (BA, S=3, F=1)Incl. rate 7 (HA, S=3, F=1)Excl. rate 7 (S=3, F=1)Excl. rate 7 (S=3, F=1)

Figure 4.30: Goodput for link adaptation with and without data rate 7

6, since the performance of data rate 7 is very close to that of 8. As a result, the datarate number 7 does have inuence on the performance of link adaptation scheme, andwe decide to include this data rate in all our simulation.The data rate number 2 and 4 might also have similar eects on the goodput of linkadaptation scheme. Investigation of such eects has not been done in this project. Thiscould be an interesting topic for future works.

4.3 Modication of link adaptation scheme

4.3.1 Our proposal

Base on our analyses in section 4.2, we propose a modied link adaptation scheme in thissection. Figure 4.31 illustrates the state-machine diagram explaining our modication:There are two key changes from the original link adaptation mechanism. First, we intendto use the value F = 2 at data rate number 7 and 8, and F = 1 for all other rates. Ifthe link adaptation could jump to rate 7 or 8, it means the quality of the link is goodand the main source of transmission failures is collision. When link adaptation changesthe STA rate from 6 to 7, it waits for one more successful transmission before changing

4.3 Modication of link adaptation scheme 73

Rate 3

DCF = BA

Rate 5Rate 6 Rate 1Rate 8

F = 2

failure

success

(f>=F)

success

(f>=F)failure F = 1 DCF = HA

success

failure(f>=F)

Rate 7

success

success(s>=S)

failure(f>=F)

success(s>=S)

failure(f>=F)

(s>=S)(s>=S) (s>=S)

Figure 4.31: Proposed modication of the link adaptation scheme

the value of F to 2. This is to ensure the link quality is indeed favourable for data rate7. However, if the next transmission fails, then we fall back to the previous data rate,and keep using the value F = 1.Secondly, we want to switch to handshaking access method whenever it appears to theSTA that the link quality is bad or collision probability is very high in the medium. Ifthe quality of the link is getting worse, it is possible that the distance between two com-municating STAs has increased or something has disturbed their communication path.In both cases, hidden terminal problem is likely to occur, and the collision probabilitywould increase if handshaking access method is not used. When the probability of colli-sion is high (for example, due to too many STAs sharing the medium at the same time),using RTS/CTS access method can further reduce the time for retransmitting the largedata packet. The modied link adaptation scheme employs handshaking access methodfor data rate 1 and 3, while basic access method are applied for data rate 5, 6, 7 and8. This is to ensure that, at large distance, where lower data rate is often selected, thehandshaking access mechanism will be used to mitigate hidden terminal problems. Inaddition, when no hidden terminals presents, at low data rate, the dierence betweengoodput of handshaking access method and that of basic access method is relativelysmall (see Figure 4.18).

4.3.2 Performance analysis

In this section, we evaluate the performance of the modied link adaptation scheme.The total goodput of this scheme is plotted against those of original link adaptationwith dierent sets of parameters in Figure 4.32. In this simulation, environment A,scenario I and packet size of 1000 bytes are used.As we can see from the Figure 4.32, the modied link adaptation outperformed theoriginal schemes at short distance, due to the fact that F = 2 is used with data ratesnumber 7 and 8. After that, its goodput decreases gradually with distance, and ap-proaches the goodput of the original link adaptation scheme using handshaking access


0 5 10 15 20 25 300

5

10

15

20

Distance (m)

Goo

dput

(M

bps)

Total goodput for modified link adaptation scheme(Scenario I, Environment A, Pksize = 1000 bytes)

BA, S=3, F=1BA, S=10, F=1BA, S=3, F=2HA, S=3, F=1HA, S=10, F=1HA, S=3, F=2Modified scheme

Figure 4.32: Total goodput for modied link adaptation scheme

method at distance greater than 15 meters. This is because RTS/CTS access methodis applied at rates 1 and 3.

In Figure 4.33 and 4.34, the simulation scenario II is employed for evaluation. Therst gure shows the average goodput of the modied link adaptation scheme, whilethe latter presents the average transfer delay of that scheme. To ease comparison, theperformance of original link adaptation scheme (S = 3, F = 2) with both basic accessand handshaking access methods are also plotted in the gures.

The average goodput of modied link adaptation is similar to that of original schemewith handshaking access method in Figure 4.33. At large distance, the modied schemeis still able to sustain signicant goodput, owing to the usage of handshaking accessmethod at data rate 1 and 3.

Analogously, the transfer delay of modied link adaptation is close to existing schemewith handshaking access method in Figure 4.34. However, at short distance, the modiedscheme shows lower average transfer delay, due to the fact that its goodput is muchhigher than that of original scheme with handshaking access method at close distance(see Figure 4.32).

In conclusion, the modied link adaptation scheme has been shown to oer high goodputat close distance, and, at the same time, to be able to avoid hidden terminal problem,

4.3 Modication of link adaptation scheme 75

0 5 10 15 20 25 300

0.2

0.4

0.6

0.8

1

Distance (m)

Ave

rage

goo

dput

(M

bps)

Average goodput for link adaptation in simulation scenario II(Environment A, Pksize=1000 bytes)

LA−BA, (S=3, F=1)LA−HA, (S=3, F=1)Modified LA

Figure 4.33: Average goodput for modied link adaptation scheme

0 5 10 15 20 25 300

1000

2000

3000

4000

5000

6000

Distance (m)

Ave

rage

tran

sfer

del

ay (

ms)

Average transfer delay for link adaptation in simulation scenario II(Environment A, Pksize=1000 bytes)

LA−BA, (S=3, F=1)LA−HA, (S=3, F=1)Modified LA

Figure 4.34: Average transfer delay for modied link adaptation scheme


maintaining a considerable average goodput at large distance. Nevertheless, the perfor-mance of this proposed scheme needs to be examined more carefully in other scenarios,especially those with faster rate of change of channel characteristics or having dissimilardistances between STAs and the AP. Due to time constrain, such evaluations of thisscheme are left for future works.

4.4 Summaries

This chapter presents the insightful descriptions of our Matlab simulator, which aimsat analysing the performance of the IEEE 802.11a standard under realistic multipathchannel models.In this chapter, we also discuss our analyses on results obtained from the simulation.Our analyses are focused on three topics: (a) performance of the IEEE 802.11a PHYlayer, (b) performance of the standard MAC layer, and (c) performance of the linkadaptation scheme proposed in [5].According to our analyses, we propose two possible modications for the link adaptationscheme. These modications are proved to inherit many advantages from the originlink adaptation schemes. The modied link adaptation oers better goodput at closedistance, while maintain signicant goodput at large distance.

Chapter

5Conclusions and future works

5.1 Conclusions

The WLAN technologies, which aim at replacing the traditional wired LAN, are ex-periencing dramatic growth in the recent years. As a promising international WLANstandard, the IEEE 802.11a is currently receiving a lot of attention from researchersall over the world. However, many researchers have assumed error-free or simple inde-pendent uniformly-distributed bit errors in the channel. These simple assumptions arenot applicable in the real usage scenario of WLAN, as WLAN connection often suersfrom time-varying frequency-selective fading channel, making its bit and packet errorpatterns more complicated.This project, Link adaptation for IEEE 802.11aWLAN over fading channel , iscarried out by Mobile Communications Group 992 at the 9th semester at Aalborg Univer-sity. In this project, we develop a IEEE 802.11a simulator with the following objectives:(a) to analyse the performance of the IEEE 802.11a under practical frequency-selectivefading channel models, and (b) to validate the performance of a simple link adaptationscheme proposed in [5] and to discuss possible modications. Based on simulation re-sults, we have obtained several interesting conclusions which will be summarised in thissection.

5.1.1 The IEEE 802.11a PHY layer

First, we can see that the OFDM technique, which is employed at IEEE 802.11a PHYlayer, has several advantages compared to the traditional single-carrier modulation. Inaddition to its spectrum eciency, OFDM is more robust to frequency-selective fadingchannel. In fact, it can eectively turn the frequency-selective fading channels into aat fading ones, with a reasonable implementation complexity.Secondly, dierent environments can aect the PER performance of the PHY layerdierently. In general, the PER performance in any environment with small delay spreadis better than that of the environment with large delay spread at low SNR region. Thisis because, in an environment with small delay spread, the bit errors tend to concentrateon some packets, leaving other packets error-free or having very little bit errors. While

77

78 Conclusions and future works

their uncoded BERs are similar, the Rayleigh at fading channel, environment A andenvironment E have huge dierences in terms of both uncoded and coded PER. Thisagain proves that using Rayleigh at fading channel to evaluate the IEEE 802.11a MAClayer performance is an optimistic assumption, because the practical scenario wouldgenerally perform much worse.Thirdly, we observe that the coded PER performance of PHY layer is generally degradedwhen higher data rate is used. This is obvious, as higher order modulation schemes,such as 16-QAM or 64-QAM, are more sensitive to noise than BPSK, and higher ratecodes, such as 2/3 or 3/4, do not have the same capability of correcting bit errors as1/2 rate convolutional code. Nevertheless, data rates number 2, 4 and 7 have no or verylittle performance gain compared to those of rates 3, 5 and 8. This makes their MAClayer goodputs indierent from the goodputs due to the data rates 3, 5 and 8.Finally, we analyse the impact of packet size on the coded PER performance of the IEEE802.11a PHY layer. Naturally, the larger the packet size, the higher the coded PER is.Small frames, such as RTS, CTS or ACK, have greater chance of being received suc-cessfully. On the other hand, large data frame are much less reliable. However, a largerpacket size also means a smaller ratio between overhead information and useful datawithin one packet. Thus, the choice of packet size is a trade-o between transmissioneciency and probability of packet error.

5.1.2 The IEEE 802.11a MAC layer

Obviously, the performance of MAC layer depends greatly on which data rate is usedat PHY layer. We observe that low data rate, while cannot provide high goodput, isable to achieve reliable connection even at large distance. In contrast, higher data rate,which oers excellent goodput at close distance, performs very poorly at long distance.This is also true for the average transfer delay. As a result, it is desirable that the STAhas a link adaptation algorithm, which selects the optimum data rate for transmissionaccording to the instantaneous link quality.One interesting observation is the collision probability obtained from our simulation.The collision is more likely to happen at short distance than at large distance, and forlow data rate than for high data rate, in case of no hidden terminal problem. The betterthe link quality, the more likely that collision will occur, due to small average value ofCW .The choice of basic or handshaking access method does have inuence on the perfor-mance of the IEEE 802.11a MAC layer. If there is no hidden terminal problem, thehandshaking access method oers slightly lower goodput (or equivalently higher trans-fer delay) than that of the basic access method at packet size of 1000 bytes. How-ever, if hidden terminal problem occurs, the handshaking access method with virtual

5.1 Conclusions 79

carrier-sensing mechanism can keep very low collision probability, resulting in a betterthroughput than the basic access scheme.Lastly, the eects of dierent environments on the performance of the MAC layer arestudied. Due to the fact that environment A has slightly lower coded PER, its MAClayer performance is higher compared to environment E, for both basic and handshakingaccess methods, at large distance. At close distance, where the SNR is high enough toconsider error-free channel, the goodputs for both environments approach the maximumgoodput of the IEEE 802.11a MAC layer.

5.1.3 Link adaptation scheme

The simple link adaptation scheme introduced in [5] relies solely on the 802.11 errorrecovery procedure at the transmitter side, and therefore can be implemented withoutany change or enhancement to the IEEE 802.11 standard. In this project, the perfor-mance of this link adaptation scheme under practical frequency-selective fading channelis evaluated using two dierent simulation scenarios: scenario I represents the best-casescenario, while scenario II depicts a typical usage scenario of a WLAN system. Thetrac model used in scenario I is balanced and fully loaded, while a constant 1Mbpsload with exponentially-distributed packet inter-arrival time is employed in scenario II.The eects of the parameters of link adaptation scheme, S and F , are also examined bysimulation.First, a large value of S generally provides much lower goodput than a small value of S.This is due to the fact that large value of S cannot react fast enough to the improvementof the link quality, i.e. the STA will maintain a low transmission rate although the qualityof the link has improved. However, at large distance, where only the lowest data rateis possible, large value of S can sometimes lead to slightly better goodput, because itcan avoid ineective switching to higher data rate when the channel has not improved.For a slowly-changing channel, large value of S is also said to be eective for the samereason.Second, while a small value of F is applicable at large distance, a large value of F issuitable for close distance, where collision is the main cause of transmission failure. Thelarge value of F is superior in this case, because it reduces the probability of falling backto lower data rate incorrectly due to collision.The simulation results obtained from scenario II indicate that the link adaptation usingbasic access method experiences severe degradation due to hidden terminal problem.This observation stimulates the idea of a link adaptation scheme that uses both basic andhandshaking access methods alternatively to achieve higher throughput at all distance.Our simulation shows that the data rate 7 does have some inuence on the performanceof link adaptation scheme. At close distance, link adaptation scheme with rate 7 gen-

80 Conclusions and future works

erally oers better goodput than that of scheme without rate 7. This is an analogouseect as using F = 2 when collision is the main source of transmission failure.

5.1.4 Modication of link adaptation scheme

From our analyses, we propose two possible modications for the above-mentioned linkadaptation scheme. First, the value F = 2 is used for data rate number 7 and 8, andF = 1 for all other rates. This is to avoid falling back to lower rate due to collision.Secondly, we switch to RTS/CTS access method whenever it appears to the STA thatthe link quality has deteriorated or the collision probability is very high in the medium.To do this, the RTS/CTS access method is employed for data rate 1 and 3, and theother rates use basic access method.The performance of modied link adaptation scheme is also evaluated with simulationscenario I and II, and compared to those of original scheme. The modied link adap-tation scheme oers higher goodput at close distance and, at the same time, is able tomaintain a signicant throughput under presence of the hidden terminal problem.

5.2 Future works

The project can continue with more extensive studies on both original and modied linkadaptation schemes. The performance of such schemes needs to be analysed carefullyin other scenarios, especially those with faster rate of change of channel characteristics,or having dissimilar distances between the STAs and the AP, or including the mobilityof STAs. The eects of data rate number 2 and 4 on the throughput of link adaptationscheme is also an interesting subject for further investigation.In this project, we have developed a complete simulator for both IEEE 802.11a PHY andMAC layers. Thus, it could be the foundation for investigation of new techniques, such aspacket combining, or for doing research at higher level of Open System Interconnection(OSI) model, for example performance of TCP/IP over IEEE 802.11a.

Bibliography[1] Teletrac Engineering Handbook; ITU-D SG 2/16 and ITC; Draft 2001-06-20.

www.tele.dtu.dk/teletrac.

[2] High-speed physical layer in the 5Ghz band - Supplement to IEEE std 802.11:Part 11: Wireless LAN medium access control (MAC) and physical layer (PHY)specications. ANSI/IEEE Std 802.11, 1999.

[3] Part 11: Wireless LAN medium access control (MAC) and physical layer (PHY)specications. ANSI/IEEE Std 802.11, 1999.

[4] David Chase. Code combining - A maximum-likelihood decoding approach forcombining an arbitrary number of noisy packets. IEEE Transactions on Commu-nications, 1985.

[5] P. Chevillat, J. Jelitto, A. Noll Barreto, and H.L. Truong. A dynamic link adapta-tion algorithm for IEEE 802.11a wireless LANs. IBM Research Report, December2002.

[6] Matthew S. Gast. 802.11 Wireless Networks: The denitive guide. O'Reilly &Associates Inc., April 2002.

[7] CEPT/ECC Working Group. ECC Guidance Document on 5Ghz Wireless LANs.Technical report, The Radio and Telecommunications Terminal Equipment Com-pliance Association.

[8] IEEE 802.11 Working Groups. Status of the IEEE 802.11 standards.www.uninett.no/wlan/ieee80211x.html.

[9] Juha Heiskala and John Terry. OFDM Wireless LANs: A Theoretical and PracticalGuide. Sams Publishing, Indianapolis, Indiana, 2002.

[10] Nguyen C. Huan, Nguyen T. Tung, and Nguyen T. Duc. Bit and packet error ratesin Rayleigh fading channels with and without diversity. Department of Communi-cation Technology, Aalborg University, June 2003.

[11] William C. Jakes. Microwave mobile communications. IEEE Press, 1974.

[12] J.Medbo and J-E. Berg. Measured radiowave propagation characteristics at 5Ghzfor typical HIPERLAN/2 scenarios. ETSI/BRAN document No. 3ERIO84A.

[13] J.Medbo and P.Schramm. Channel models for HIPERLAN/2. ETSI/BRAN docu-ment No. 3ERI085B.

81

82 BIBLIOGRAPHY

[14] Hagenauer Joacho. Rate-compatible punctured convolutional codes (RCPC codes)and their applications. IEEE Transactions on Communications, 1998.

[15] Samir Kallel. Complementary punctured convolutional (CPC) codes and their ap-plications. IEEE Transactions on Communications, 1995.

[16] Samir Kallel and David Haccoun. Sequential decoding with ARQ and code combin-ing: A robust hybrid FEC/ARQ system. IEEE Transactions on Communications,1988.

[17] A. Kamerman and L. Montean. WaveLAN-II: A high-performance wireless LANfor the Unlicensed Band. Bell Labs Technical J., 1997.

[18] Eric Weisstein: The World of Mathematics. Exponential distribution.http://mathworld.wolfram.com/ExponentialDistribution.html.

[19] J. D. Parsons. The Mobile Radio Propagation Channel. John Wiley & Sons Ltd.,2000.

[20] Daji Qiao, Sunghuyn Choi, and Kang G. Shin. Goodput analysis and link adap-tation for IEEE 802.11a wireless LANs. IEEE Transactions on Mobile Computing,2002.

[21] Theodore S. Rappaport. Wireless communications: Principles and Practice. Pren-tice Hall PTR.

[22] Bernard Sklar. Rayleigh fading channels in mobile digital communication systems- Part I: Characterization. IEEE Communications Magazine, page 136, September1997.

[23] Gordon L. Stüber. Principles of mobile communication. Kluwer Academic Publish-ers, 2001.

[24] Richard van Nee and Ramjee Prasad. OFDM Wireless Multimedia Communica-tions. Artech House, 2000.

[25] S.B. Weinstain and P.M. Elbert. Data transmission by frequency division multi-plexing using the discrete Fourier transform. IEEE Trans. Comm., 1971.

[26] Jui-Hung Yeh, Jyh-Cheng Chen, and Chi-Chen Lee. WLAN standards: in partic-ular, the IEEE 802.11 family. http://wire.cs.nthu.edu.tw/wire1x/nal-gallery.pdf.

Appendix

AList of symbols

A : The peak amplitude of the dominant signalaAirPropagationT ime : The time it takes a transmitted signal to go from the

transmitting STA to the receiving STAaMACProcessingT ime : The nominal time the MAC uses to process a frame and

prepare a response to the frameaSlotT ime : The slot-time valueBc : Coherent bandwidth of the channelBD : Doppler spreadCW : The contention windowsCn(t) : Time variant amplitude of the received signal associated

with the nth coming waved : Distance between the receiver and the antennad0 : The reference distance of the antennaEnv : Type of channel modelsfD,n : Doppler frequency shiftfm : Maximum Doppler frequencyfc : Carrier frequencyfΩ(r) : The phase of the complex gain of at fadingg(t) : Complex gain of the at fading channelgn(t) : The time-variant complex gainh(t, τ), h(τ) : Impulse response of the multi-path channelI0(.) : The modied Bessel function of the rst kind and zero

orderK : K factor, describing the Ricean distributionKMOD : The normalised factor in a modulation schemeLfs(d) : Attenuation factorM : Number of scattering pathsn : Path loss exponential factorn(t) : The additive white Gaussian noiseNSD : Number of data subcarriersNSP : Number of pilot subcarriersNST : Total number of subcarriers

83

84 List of symbols

PDP (.) : Power Delay Prole functionPksize : Size of PSDUPTX : Transmitting powerPNOISE : Level of noise oorPRX : Usable range of received powerPL(d) : Path loss as a function of distance d

PLfs(d) : Free-space path loss at distance d

Pt : Transmitted powerPr(d) : Received power at distance d

R : Rate of the convolutional codeRn(τ) : Auto-Correlation Function of noise source n(t)

r(t) : Transmitted signal in passbandr(t) : Transmitted signal in basebands(t) : Received signals(t) : Received signal in basebandSn(f) : Power Spectral Density of n(t)

SP (f) : Spectral response (or Magnitude frequency response)SNRmin : Minimum SNR levelTc : Coherence time of the channelTdet : The duration for STA to detect the transmission from

another STATs : Symbol periodTFFT : IFFT/FFT periodTPREAMBLE : PLCP preamble durationTSIGNAL : Duration of the SIGNAL BPSK OFDM symbolTGI : GI durationTGI2 : Training symbol GI durationTSY M : Symbol intervalTSHORT : Short training sequence durationTLONG : Long training sequence durationXσ : Zero-mean Gaussian distributed random variable with

standard deviationX(t) : White Gaussian noise in basebandv : Velocity∆ : Mean excess delay∆ : The excess delay∆max : The maximum excess delay∆n : The excess delay of the nth tap∆F : Subcarrier frequency spacingτ : Delay of the incoming multi-path component

85

τc : Time delay for all scattering paths from the transmitterto the receiver

τn(t) : Time delay of signal associated with the nth multi-pathcomponent

Φn(t) : Phase associated with the nth in coming pathθn : AoA of the nth incoming waveµ : Mean packet inter-arrival timeΩ : The short-term envelope of the complex at fading gainσ2

Ω : The mean power of the complex at fading gainσ∆ : rms delay spreadσ(τ) : Weighted delta functionλ : Wavelength of the signalδ(.) : Dirac delta functionΨi(t) : the ith subcarrier of the OFDM symbol

Appendix

BList of acronyms

ACF Auto-Correlation Function

ACK Acknowledgement

A/D Analog to Digital

AM Amplitude Modulation

ARF Auto-Rate Fallback

ARQ Automatic Repeat Request

AoA Angle of Arrival

AP Access Point

AWGN Additive White Gaussian Noise

BER Bit Error Rate

BPF Band Pass Filter

BPSK Binary Phase Shift Keying

BS Base Station

BSC Binary Symmetric Channel

CCF Cross-Correlation Function

CDF Cumulative Distribution Function

CDMA Code Division Multiple Access

CSMA/CA Carrier Sense Multiple Access / Collision Avoidance

CPC Complementary Punctured Codes

CTS Clear-To-Send

87

88 List of acronyms

D/A Digital to Analog

DC Direct Current

DCF Distributed Coordination Function

DIFS DCF Inter-Frame Spacing

DFS Dynamic Frequency Selection

DSSS Direct Sequence Spread Spectrum

EIFS Extended Inter-Frame Spacing

EGC Equal Gain Combining

ETSI European Telecommunications Standards Institute

FEC Forward Error Correction

FCS Frame Check Sequence

FDM Frequency Division Multiplex

FFT Fast Fourier Transform

FHSS Frequency Hopping Spread Spectrum

FM Frequency Modulation

FTM Fourier transform method

ICI Inter-Channel Interference

IEEE Institute of Electrical and Electronic Engineers

IDFT Inverse Discrete Fourier Transform

IFFT Inverse Fast Fourier Transform

IFS Inter-Frame Spacing

ISI Inter-Symbol Interference

ISM Industrial, Scientic and Medical

GBN Go-back-N

GF Galois Field

89

GI Guard Interval

GMSK Gaussian Minimum Shift Keying

GSM Global System for Mobile communication

HIPERLAN HIgh PErformance Radio LAN

HiSWAN High Speed Wireless Access Network

HPF High Pass Filter

LAN Local Area Network

LFSR Linear Feedback Shift Register

LLC Logical Link Control

LOS Line Of Sight

LPF Low Pass Filter

NAV Network Allocation Vector

NRZ Non-Return Zero

m-sequence Maximal-length sequence

MAC Medium Access Control

MAP Maximum a posteriori

MMAC Multimedia Mobile Access Communication

MRC Maximal Ratio Combining

MPDU MAC Protocol Data Unit

MPM Markov process method

MS Mobile Station

NLOS No Line Of Sight

OFDM Orthogonal Frequency Division Multiplex

OSI Open System Interconnection

PAP Peak-to-Average Power

90 List of acronyms

PCF Point Coordination Function

PDF Probability Density Function

PDP Power Delay Prole

PSD Power Spectral Density

PER Packet Error Rate

PIFS PCF Inter-Frame Spacing

PHY Physical Layer

PLCP Physical Layer Convergence Procedure

PM Phase Modulation

PMD Physical Medium Dependent

PPDU PLCP Protocol Data Unit

PSDU PHY Sublayer Service Data Unit

P/S Parallel to Serial

PSK Phase Shift Keying

QAM Quadrature Amplitude Modulation

QoS Quality of Service

QPSK Quadrature Phase Shift Keying

RCPC Rate-Compatible Punctured Codes

RF Radio Frequency

RTS Request-To-Send

rms root mean square

SC Selection Combining

SIFS Short Inter-Frame Spacing

SNR Signal to Noise Ratio

S/P Serial to Parallel

91

SR Selective Repeat

SW Stop-and-Wait

STA Station

TDMA Time Division Multiple Access

TPC Transmission Power Control

WEP Wired Equivalent Privacy

WLAN Wireless Local Area Network

WSS Wide Sense Stationary

UHF Ultra High Frequency

U-NII Unlicensed - National Information Infrastructure

Appendix

CThe principles of OFDM technique

The frequency-selective fading channel occurs when the bandwidth of the transmittedsignal is larger than the channel coherence bandwidth. Thus, if we can divide thetotal bandwidth of transmitted signal into several fractions, each of which is less thanthe coherence bandwidth of the channel, then those sub-channels only experience atfading condition. In other words, we can apply the well-known Frequency DivisionMultiplex (FDM) technique to turn the frequency-selective fading channel into a atfading one, improving the performance of the transmission link.In classical FDM transmitter, the high-speed data stream is rst divided into NSD

parallel streams, which are running at 1/NSD the rate of original one. These streams arethen modulated onto NSD non-overlapping frequency subcarriers. Figure C.1 shows thespectrum of the FDM system. Typically, in FDM system, there is a need for guard bandsbetween dierent subcarriers to prevent ICI. This leads to inecient use of availablespectrum in FDM technique.The OFDM can be seen as an enhanced version of FDM, where its subcarriers are al-lowed to overlap. Figure C.1 illustrates the dierence between conventional FDM andOFDM techniques, and it is clear that we can save a lot of bandwidth by using the over-lapping subcarriers. Overlapping is possible in OFDM system, because its subcarriersare orthogonal with each other, which is explained in details later. The information ismodulated onto a subcarrier by adjusting the subcarrier's phase, amplitude or both.An OFDM signal consists of a sum of subcarriers that are modulated using Phase ShiftKeying (PSK) or QAM. If di are the complex PSK or QAM symbols, NSD is the numberof subcarriers, T is the symbol duration and fc is the carrier frequency, then one OFDMsymbol starting at t = ts can be expressed as [24]:

r(t) =

∑NSD2−1

i=−NSD2

di+

NSD2

exp[j2π i

T(t− ts)

]ts ≤ t ≤ ts + T

0 otherwise(C.1)

where r(t) is the complex baseband OFDM symbol, and Ψi(t) = exp[j2π iT(t − ts)] is

the ith subcarrier of the OFDM symbol, where i = −NSD

2, . . . , NSD

2+ 1. Note that each

subcarrier has exactly an integer number of cycles in the interval T , and the number

93

94 The principles of OFDM technique

Figure C.1: The spectrums of (a) conventional FDM and (b) OFDM technique

of cycles between adjacent subcarriers diers by exactly one. Due to this property, thesubcarriers are 'orthogonal' with each other, i.e. they pass the orthogonality test:

∫ ts+T

ts

Ψi(t)Ψ∗j(t)dt =

∫ ts+T

ts

exp[j2πi− j

T(t− ts)]dt

=

T i = j

0 i 6= j(C.2)

The orthogonal property of subcarriers enables us to obtain the modulated data fromeach subcarrier individually, even though they are overlapping. For example, to de-modulate the jth subcarrier from Equation (C.1), we rst downconvert the signal witha frequency of j/T and then integrate the signal over T seconds. The result of theseoperations is the desired output d

j+NSD

2

(multiplied by a constant factor T ), as shown

95

in Equation (C.3).

∫ ts+T

ts

exp[−j2πj

T(t− ts)]

NSD2−1∑

i=−NSD2

di+

NSD2

exp[j2πi

T(t− ts)]dt =

NSD2−1∑

i=−NSD2

di+

NSD2

∫ ts+T

ts

exp[j2πi− j

T(t− ts)] = d

j+NSD

2

T (C.3)

Figure C.2: Block diagrams of (a) OFDM modulator and (b) OFDM demodulator

Figure C.2 illustrates the direct implementation of the OFDM modulator and demodu-lator. In this early design, a large array of sinusoidal generators and also a large bankof coherent demodulator with high frequency accuracy are required in order to make itwork. This requirement is dicult to achieve, and it made OFDM technology complexand unattractive. Fortunately, Weinstein and Ebert [25] has derived another form forimplementing the OFDM system in 1971. The complex baseband OFDM signal as de-ned by Equation (C.1) is in fact nothing more than the inverse Fourier transform ofNSD PSK or QAM symbols. The discrete-time equivalent is the Inverse Discrete FourierTransform (IDFT), which is given in Equation C.4, where the time t is replaced by asample index n [24].

r(n) =

NSD−1∑i=0

di exp[j2π

in

T

]

= IDFT (di) for i = 0, 1, . . . , NSD − 1 (C.4)

In practice, the IDFT can be implemented very eciently by the IFFT. The only re-quirement is that the number of subcarriers, NSD, must be in the power of 2. Thebanks of sinusoidal generators and coherent demodulators in Figure C.2 are now re-placed by IFFT and FFT operators, respectively. Today, the availability of fast and


cheap IFFT/FFT processors has made OFDM technique a favourable choice for manywireless applications, such as digital television broadcasting, WLAN and the future 4th

generation wireless network.

C.1 The block diagram of OFDM system

In this section, we are going to discuss the implementation of the OFDM system in moredetails. A typical implementation of OFDM system is represented in Figure C.3. Aswe have mentioned earlier, the binary data is rst mapped into PSK or QAM symbolsvia mapping module. The symbol stream is then divided into NSD parallel sub-streamsby the S/P converter, and transformed into time-domain by IFFT operation. The P/Sconverter combines the parallel signals into OFDM symbols.

Figure C.3: Block diagrams of OFDM system based on IFFT/FFT technique

A guard interval (or guard time) between OFDM symbols is necessary to remove ISI.Figure C.4 shows that, without the guard interval, the rst OFDM symbol will interferewith the second one, due to multipath delay. If a guard interval larger than the expecteddelay spread is inserted between two OFDM symbols, the interference will not aect thenext symbol. The guard interval, TGUARD, could consist of no signal at all. However, thiszero guard interval causes ICI, i.e. subcarriers are no longer orthogonal and crosstalkbetween dierent subcarriers happens. In order to eliminate ICI, the OFDM symbolis cyclically extended in the guard interval. This ensures that delayed replicas of theOFDM symbols always have an integer number of cycles within the FFT interval, aslong as the delay is smaller than the guard time [24]. This whole process is referred toas 'cyclic prex insertion' in the block diagram.To further optimise the spectrum of the transmitted signal, windowing can be appliedto the individual OFDM symbols. Windowing an OFDM symbol makes the amplitudego smoothly to zero at the symbol boundaries (see Figure C.5). This procedure helpsto greatly reduce the spectrum sidelopes of transmitted signal [24].At the receiver, reverse operations are performed to achieve the transmitted binary data.First, the cyclic prex is removed from received signal. The FFT operation is applied

C.1 The block diagram of OFDM system 97

Figure C.4: The eect of guard time between OFDM symbols: (a) Without guard time, and (b) With guard time

Figure C.5: The cyclic prex insertion and windowing processes


on the received OFDM stream. Finally, demapping block converts the obtained PSK orQAM symbols back to binary stream.

C.2 Consideration of OFDM parameters

The parameters of OFDM system are selected based on three main requirements, namelybandwidth, bit rate and delay spread.

First of all, the delay spread directly controls the length of the guard interval. As a rule,the guard time should at least be about two or four times the rms delay spread. Thisvalue depends on the type of coding and modulation schemes, because higher orderQAM (such as 64-QAM) is more sensitive to ISI and ICI than BPSK; while heaviercoding obviously reduces the sensitivity to such interference [24].

If the guard interval is chosen, the symbol duration can be selected. To minimise theSNR loss due to guard interval, it is desirable to have symbol duration is much largethan the guard time. However, we cannot aord symbol duration to be too large, asa larger symbol duration means more subcarriers with a smaller subcarrier spacing,a larger implementation complexity and more sensitive to phase noise and frequency,as well as an increased Peak-to-Average Power (PAP) ratio. As a result, the symbolduration is often selected to be at least ve times of the guard interval, which implies a1dB SNR loss because of guard time [24].

Once the symbol duration is also xed, we can calculate the subcarrier spacing as theinverse of symbol duration less the guard interval. Number of subcarriers is equal to therequired bandwidth divided by the subcarrier spacing. Finally, to obtain the requiredbit rate, we can select a suitable modulation scheme and coding rates for our OFDMsystem.

C.3 Advantages and disadvantages of OFDM technique

The OFDM technique has several advantages compared to the single-carrier modulation.As we have discussed earlier, the key reasons to use OFDM are its spectrum eciencyand the ability to deal with frequency-selective fading channel with a reasonable im-plementation complexity. In a single-carrier system, the implementation complexityis dominated by the channel equalisation, which is necessary when the channel delayspread is larger than about ten percent of the symbol duration. The OFDM system doesnot required equalisation, and therefore the complexity is greatly reduced. For example,in IEEE 802.11a WLAN application, the usage of OFDM technique reduces the systemcomplexity to 1/10 compared to the equivalent single-carrier system [24].

C.3 Advantages and disadvantages of OFDM technique 99

In single-carrier system, the equalisation hardware is often built into the system and isunalterable. If the delay spread exceeds the value for which the equaliser is designedto work with, the system performance degrades abruptly. Due to error propagation inequaliser, the raw bit error probability increases so quickly that introducing lower ratecoding or a lower constellation size does not signicantly improve the situation. ForOFDM, however, there are no such nonlinear eects as error propagation, and lowerrate coding and/or lower constellation sizes can be employed to provide fall-back ratesthat are signicantly more robust against large delay spread. This feature is desirable,as it enhances the coverage area and avoids the situation that users in bad spots (e.g.having very large delay spread) cannot get any connection at all [24].The OFDM technique is also more robust to timing oset than the single-carrier sys-tem. In fact, the symbol timing oset may vary over an interval equal to the guardtime without causing ICI or ISI. Hence, OFDM is quite insensitive to timing osets.Nevertheless, any deviation from the optimum timing instant means that the sensitivityto delay spread increases, or the system can handle less delay spread than the valueit was designed for. To minimise this loss of robustness, the OFDM system should bedesigned such that the timing error is small compared with the guard interval [24].On the other hand, two main drawbacks of the OFDM technique are the high PAP ratioand sensitivity to phase noise and frequency oset. An OFDM signal consists of NSD

subcarriers, which are independently modulated. If all of those signal are in-phase, theyadd up coherently to produce a peak power that is NSD times the average power. Thishigh PAP ratio brings several disadvantages to implementation of OFDM system, suchas an increased complexity of the analog-to-digital and digital-to-analog converters, anda requirement of RF power amplier with high dynamic range [24]. However, there areseveral techniques to reduce the PAP ratio in OFDM system. For example, a specialFEC code set that excludes OFDM symbols with large PAP ratio can be applied, sothat the high PAP ratio situation can be avoided.All OFDM subcarriers are orthogonal if they all have a dierent integer number of cycleswithin the FFT interval. If there is a frequency oset between the transmitter and thereceiver, then the number of cycles in the FFT interval is not an integer anymore, withthe result that ICI occurs after the FFT. Another related problem is phase noise. Apractical oscillator does not produce a carrier at exactly on frequency, but rather acarrier that phase modulated by random phase jitter. As a result, the frequency, whichis the time derivative of the phase, is never perfectly constant and therefore causingICI in the OFDM receiver. For single-carrier system, phase noise and frequency osetsonly give a degradation in the received SNR, rather than introducing interference. Thisis the reason that the sensitivity to phase noise and frequency oset is mentioned asdisadvantages of OFDM system [24]. There are many on-going researches to nd betterfrequency synchronization techniques, using the cyclic prex or special OFDM trainingsymbols, which minimises the degradation due to frequency error.

Appendix

DWireless environments in PHY simulation

Table D.1: Model A. Corresponds to a typical oce environment for NLOS conditions and 50ns average rms delay spreadTap Delay Average Ricean Doppler

Number (ns) Relative K SpectrumPower (dB)

1 0 0.0 0 Classic2 10 -0.9 0 Classic3 20 -1.7 0 Classic4 30 -2.6 0 Classic5 40 -3.5 0 Classic6 50 -4.3 0 Classic7 60 -5.2 0 Classic8 70 -6.1 0 Classic9 80 -6.9 0 Classic10 90 -7.8 0 Classic11 110 -4.7 0 Classic12 140 -7.3 0 Classic13 170 -9.9 0 Classic14 200 -12.5 0 Classic15 240 -13.7 0 Classic16 290 -18.0 0 Classic17 340 -22.4 0 Classic18 390 -26.7 0 Classic

101

102 Wireless environments in PHY simulation

Table D.2: Model B. Corresponds to typical large open space and oce environments for NLOS conditions and 100ns

average rms delay spreadTap Delay Average Ricean Doppler


1 0 -2.6 0 Classic2 10 -3.0 0 Classic3 20 -3.5 0 Classic4 30 -3.9 0 Classic5 50 0.0 0 Classic6 80 -1.3 0 Classic7 110 -2.6 0 Classic8 140 -3.9 0 Classic9 180 -3.4 0 Classic10 230 -5.6 0 Classic11 280 -7.7 0 Classic12 330 -9.9 0 Classic13 380 -12.1 0 Classic14 430 -14.3 0 Classic15 490 -15.4 0 Classic16 560 -18.4 0 Classic17 640 -20.7 0 Classic18 730 -24.6 0 Classic

103

Table D.3: Model C. Corresponds to a typical large open space environment for NLOS conditions and 150ns average

rms delay spreadTap Delay Average Ricean Doppler


1 0 -3.3 0 Classic2 10 -3.6 0 Classic3 20 -3.9 0 Classic4 30 -4.2 0 Classic5 50 0.0 0 Classic6 80 -0.9 0 Classic7 110 -1.7 0 Classic8 140 -2.6 0 Classic9 180 -1.5 0 Classic10 230 -3.0 0 Classic11 280 -4.4 0 Classic12 330 -5.9 0 Classic13 400 -5.3 0 Classic14 490 -7.9 0 Classic15 600 -9.4 0 Classic16 730 -13.2 0 Classic17 880 -16.3 0 Classic18 1050 -21.1 0 Classic

104 Wireless environments in PHY simulation

Table D.4: Model D. Same as model C but for LOS conditions. A 10 dB spike at zero delay has been added resulting

in a rms delay spread of about 140nsTap Delay Average Ricean Doppler


1 0 -0.0 10 Classic+spike2 10 -10.0 0 Classic3 20 -10.3 0 Classic4 30 -10.6 0 Classic5 50 -6.4 0 Classic6 80 -7.2 0 Classic7 110 -8.1 0 Classic8 140 -9.0 0 Classic9 180 -7.9 0 Classic10 230 -9.4 0 Classic11 280 -10.8 0 Classic12 330 -12.3 0 Classic13 400 -11.7 0 Classic14 490 -14.3 0 Classic15 600 -15.8 0 Classic16 730 -19.6 0 Classic17 880 -22.7 0 Classic18 1050 -27.6 0 Classic

105

Table D.5: Model E. Corresponds to a typical large open space environment for NLOS conditions and 250ns average

rms delay spreadTap Delay Average Ricean Doppler


1 0 -4.9 0 Classic2 10 -5.1 0 Classic3 20 -5.2 0 Classic4 40 -0.8 0 Classic5 70 -1.3 0 Classic6 100 -1.9 0 Classic7 140 -0.3 0 Classic8 190 -1.2 0 Classic9 240 -2.1 0 Classic10 320 0.0 0 Classic11 430 -1.9 0 Classic12 560 -2.8 0 Classic13 710 -5.4 0 Classic14 880 -7.3 0 Classic15 1070 -10.6 0 Classic16 1280 -13.4 0 Classic17 1510 -17.4 0 Classic18 1760 -20.9 0 Classic

Appendix

EFlowcharts of simulation functions

In this appendix, the owcharts, which illustrate our methods of implementation of sim-ulation functions, are presented. To reduce complexity, we use Matlab matrix notationsand some basic functions in the owchart. Therefore, general understanding of Matlabis required to understand this section. The Matlab codes for these modules are alsoincluded with this report.

107

108 Flowcharts of simulation functions

Figure E.1: The Random sequence generator

Figure E.2: Binary converter module

109

Figure E.3: Convolutional coder module


Figure E.4: Interleaving module

111

Figure E.5: Symbol mapping module



113




115

Figure E.9: The Serial to parallel converter


Figure E.10: The IFFT module

Figure E.11: The Parallel to serial module

117

Figure E.12: Wideband channel module


Figure E.13: Wideband channel module

119

Figure E.14: Ricean Simulator module


Figure E.15: AWGN channel

121

Figure E.16: FFT module


Figure E.17: Symbol demapping module

123




125

Figure E.20: Deinterleaving module


Figure E.21: Viterbi decoder module

127

Figure E.22: Viterbi decoder module (cont)

Figure E.23: Coded bit error counter

Documents

Link adaptation for IEEE 802.11a WLAN over fading …kom.aau.dk/~hcn/publications/semester9.report.pdf1.1.1 Advantages and disadvantages of WLAN TheWLANtechnologiesaresosuccessfulbecauseito