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Multicarrier Communications

-Lecture 7: OFDMA Systems

Jian (Andrew) [email protected]

Wireless Signal Processing ProgramNational ICT Australia

http://users.rsise.anu.edu.au/ jian/Course mc.html

Canberra, Australia, 2007

MC 2007 cJian (Andrew) Zhang 1

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What we covered in Lecture 6

MIMO Basics

Capacity AnalysisSpace-frequency Coding

MIMO-OFDM Transceiver Design

Beamforming for MIMO-OFDM


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What will be covered in this Lecture

Basics of Multiuser Access

OFDMA Basics

OFDMA Synchronization in uplink

Synchronization mechanism in practical systems: RangingchannelSynchronization schemes (of Academic interest) [1]

Cross-layer design

Multiuser Diversity

Mobility-dependent Traffic Channels

Multi-cell Frequency Planning


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Multiuser Access

Multiple access schemes are used to allow many users to share

simultaneously a finite amount of spectrum.

The sharing of spectrum is required to achieve high capacity by

simultanously allocating the available bandwidth to multiple

users.

For high quality communications, this must be done without

severe degradation in the performance of the system.

There are many access techniques , some of them are

Frequency Division Multiple Access (FDMA)Time Division Multiple Access (TDMA)Space Division Multiple Access (SDMA)Spread Spectrum Multiple Access (SSMA): e.g., CDMA, FHMA


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Illustration of MA Schemes


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Multiple Access in OFDM Systems

OFDM-FDMA (OFDMA)

OFDM-TDMA

OFDM-CDMA (Multicarrier + CDMA)


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Advantages of OFDMA Systems

Better data rate granularity based on both time and frequency

domain resource assignmentSmaller Link budget for low rate users

Receiver Simplicity with multiuser-interference free detection

Multiuser diversity capability


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OFDMA Optimality

The capacity is approached in a multi-user multi-carrier SISO

systems when the following conditions are satisfied:

1 Each subcarrier is assigned to only one user, i.e., OFDMA;

2 The assigned user on subcarrier nhas the highest channel gainover K users;

3 The power over subcarriers is allocated using a water-filling

solution with respect to channel gains.

Similarly, OFDMA optimality can also be shown for MIMO systems.


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Downlink and Uplink

DL: One transmitter and multiple receiversUL: Several transmitters and one receiver

In UL, all transmitters have unique time and frequency offset,

thus, UL system design is more difficult than DL.

Asymmetric traffic distribution between UL and DL is alwaysexpected.


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OFDMA System Design

Factors to consider

Different users can have different mobile speed, different

channel delay spread number of subcarriers, subcarrier

interval, length of guarding interval, pilots allocation

Different users may have different data rate and QoSrequirements subchannel length, subchannel structure,

adaptive modulation and coding

Different users may have different channel impulse response

Multiuser diversity

Optimization between average system performance and

spectrum efficiency (system capacity) Intelligent Frequency

planning


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Subcarrier Allocation Strategy in OFDMA

Subband SAS

A group of adjacent subcarriers are assigned to each user;Poor freq. diversity

Interleaved SASsubcarriers of each user are uniformly spaced;Good freq. diversity, but not best multiuser diversity

Random SASAllow dynamic resource assignment and provide best multiuserpotential


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PN Sequence Design in Random SAS

N available data subcarriers are usually first grouped in blocks with

equal length Q, a permutation sequence (PN) and its cyclic versions

are then applied to assign subcarriers to users.

N = PQ, basic PN sequence {cm}, 1 cm QThe period of PN sequence can be equal to P, which is generally

the length of a subchannel.

{cm} should have good circulant auto-correlation andcross-correlation properties, to minimize intra-cell and inter-cell

interference while maximizing spectrum efficiency and frequency

reuse ratio.


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Timing and Frequency Synchronization

General progress is:

1 In downlink, MT performs freq. and timing estimation and adjust

itself for uplink transmission;2 BS estimates freq. and timing for all the users;

A challenging task as the BS receives a mix of signals eachaffected by exclusive synchronization errors;A multi-parameter estimation problem where each user must beseparated from others.

3 Timing and freq. correction in BS


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Timing in Uplink

1 BS broadcasts timing pilots and k-th MT estimates initial timing

difference p(k) + T(k), p(k): propagation delay; T(k):basic timing difference between transceiver

2

k-th MT synchronizes to BS, and transmits uplink stream;3 Signals from different users will arrive at the BS with timing

difference p(k) p(m);4 Guarding period (CP) needs to be larger than the sum of channel

delay spread and the propagation delay max(|p(k)

p(m)

|).

For systems with large covering area, propagation delay can be

comparable to the symbol period. Unacceptable!


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Quasi-synchronous Network

Some mechanisms, e.g., a Ranging channel, can be adopted to

establish an ISI-free quasi-synchronous system such that the timing

error becomes small and can be incorporated in channel estimates.

One example:

1 BS broadcasts timing pilots and k-th MT estimates initial timingdifference p(k) + T(k), p(k): propagation delay; T(k):basic timing difference between transceiver

2 k-th MT synchronizes to BS, and transmits unique timing pilots

to BS;

3 BS estimates p(k) by using correlator with known template foreach user, and send the value of k to user k;

4 User k then adjust his transmitting time by k, so that signalsfrom all users will arrive at the BS roughly at the same time.


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Ranging Channel

Ranging channel is a control channel allowing users to buildconnection with BS. Functions include

letting MT adjust its parameters (CFO, Timing, etc.) to join a

quasi-synchronized network;

Resource request and assignmentParameter tracking

Power measurement/Power control and Handover

Research problems:

Optimal resource configuration of ranging channel

Timing and CFO estimation based on pilots in ranging channel

Ranging code design


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Ranging Channel - An Example


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Synchronization with Subband SAS

If CFO is smaller than the subcarrier guard intervals, users

signals can be separated by passing the received samplesthrough a bank of digital band-pass filters, each selecting one

subband.

General sync algorithms can then be applied independently for

each user.

Perfect users separation cannot be achieved in practice as this

would require ideal brickwall filters and/or large guard intervals.


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CFO Estimation with Interleaved SAS

Each users block has a periodic structure. For m-th user

occupying P subcarriers {im + pL; 0 p P 1}, at distance L,

sm(k) = ej2n(im+m)/L

sm(k + P), 0 L 1. (1)

This signal model motivates the use of Spectrum Analysis

algorithms, e.g., MUSIC, ESPRIT and Matric pencil, to estimate

the CFO term m.


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CFO Estimation with random SAS

Research still in very early stage.

ML estimation is developed based on training blocks;

Complexity forbids its implementation in practice.


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Timing and CFO Compensation in uplink

1 Estimates are returned to MTs which adjust its parameters

accordingly.2 Compensation in BS directly by applying advanced algorithms

Independent compensation for each user in Subband SASFrequency compensation through Interference CancellationFrequency compensation through Linear Multiuser Detection


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Cross-layer Design

Cross-layer design: Joint optimization multiple layers in system

design. Why cross-layer design?

In broadband networks, traffic is highly diverse with distinct QoS

parameters, delay sensitivity and error-sensitivity, channel may

vary dramatically, and user pattern presents high dynamics inmobility.

Decoupled layer design which copes with the worst case

condition will lead to very inefficient usage of spectrum and

energy.Protocols with multi-layer adaptability can adapt to the service

variations and achieve high spectrum efficiency.


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Cross-layer Design Issues in OFDMA

Multiuser diversity

Mobility-dependent Traffic Channels

fixed-portable applications: slow fading; low signalling overheadwith occasional feedback Multiuser diversity suitableMobile applications: fast fading; intensive overhead for resourceallocation Frequency diversity suitable

Adaptive Modulation and Coding

Scheduling


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Multiuser Diversity

In a wireless system with many users, the utility value (data rate,

channel) of a given resource unit varies from one user to another.

Such fluctuation allow the overall system performance to be

maximized by allocating each radio resource unit to the user that

can best exploit it.

It can be proven that intelligent resource allocation renders

performance improvement (e.g., expected transmission rate per

subcarrier), and the improvement increases with the number of

users.The system performance improvement due to the increase in the

number of users is referred as multiuser diversity gain.


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Where is Multiuser Diversity available

Service-enabled: difference in data rate and QoS - Granularity

related

Mobility-enabled multiuser diversity in relay networks

Space-enabled multiuser diversity in SDMA

Frequency-selectivity enabled multiuser diversity in OFDMA


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Multiuser Diversity in OFDMA

Channel fading is statistically independent for different MTs, as long

as their receive antennas are separated considerably. Similarity

between MIMO-OFDM and MISO-OFDMA

Water-filling algorithms

Finite Tones Water-filling

Loading algorithms

Algorithms to realize multiuser diversity in OFDMA will be discussed

in Lecture 8.


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Mobility-dependent Traffic channels

Traffic channels (subchannels)

Multiuser diversity (MD) and Frequency diversity (FD) is atradeoff in OFDMA systems.

MD provides more performance improvement than FD;MD and FD have different requirement on the distribution ofsubcarriers in a subchannel.


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Subchannel configuration for fixed/portable

applications

Clusters should be grouped as tight as possible to enable higher

multiuser diversity, leading to higher aggregated rate;

Small subchannel sizes are preferred - the multiuser diversity

gain can be readily captured with simple progressive channel

allocation scheme.


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Subchannel configuration for mobile applications

Larger subchannels are preferred to provide better frequencydiversity and, thus, higher outage capacity;

For applications with small outage probability requirements, the

clusters should be distributed to enable higher frequency

diversity; the opposite is true for applications that can toleratehigh outage probabilities.

For mixed applications, the ideal system platform should be able

to support both small and tight traffic channels with maximum

multiuser diversity and large and loose traffic channels with

maximum frequency diversity.

The partition can be optimized based on the ration of low

mobility and high mobility users.


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802.16e traffic channels

IEEE 802.16e defines three types of subchannel configuration

Fully used subchannelization (FUSC) and Partially usedsubchannelization (PUSC) - loose and distributed configuration

for mobile channels to maximize FD

Advanced modulation and coding subchannel (AMC) - tight and

adjacent channel configuration for fixed applications to maximize

MDZone Switching allows dynamic configuration of PUSC, FUSC

and AMC in a frame.


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Multi-cell Frequency Planning [2]

Frequency resue: Same set of frequency bands can be reused by

multiple base stations as long as the cochannel interference is

tolerable.

Classification of Frequency planning schemes

Static/fixed frequency chanell allocation (FCA)

Adaptive/Dynamic channel allocation (DCA)

Combination of FCA and DCA


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Fixed Channel Allocation

Total number of channels are divided into disjoint groups and

assigned to cells. Planning in the system setup and installation stageand slight adjustment in the system operation process.

For Hexagonal cells, we have

reuse distance ratio =Reuse distance

Cell radius=

3

cluster size (2)

where cluster size is the minimum number of neighboring cells

that are assigned the entire set of channels.

In a given area and a fixed cell size, smaller cluster size leads to

higher capacity.Factors to consider in FCA

CapacityDesired SIR in user terminalsTraffic loads (e.g., Irregular FCA for unevenly loaded traffic)


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Dynamic Channel Allocation

Channel distribution adapts over time during system operation.

Centralized DCA in central controller: Excellent performance

with intensive signaling and computational complexity

Distributed DCA in BSs or MTs, independently or cooperativelyDCA in OFDMA is very challenging because

SINR criterion changed from predetermined to varied

Channels changed from flat fading to frequency selective fading

Computation complexity increased significantly due to thesubcarrier-based planning


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OFDMA DCA: an Example

DCA realized by the coordination of central controller (e.g., RNC)

BSs and MTs. Signalling overhead and computation complexity areboth reduced.

Using beacon signals from BSs, each MT determines the

dominant interfering BS, and the achievable rates with and

without the dominant interference, and feedbacks the information

to BSs and then to RNC;

RNC updates all users CSI every super-frame, performs

interference avoidance, and determines specific set of

subchannels assigned to each BS and the recommended user

assignment for each BS;BS makes actual pairing between the traffic bearers and the

users. When a user recommended by RNC has traffic to send,

BS follows RNCs suggestions, otherwise, BS performs owns

channel adaptation.


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Inspiration on Research work

Feedback channel is usually present in modern systems

Design and exploit feedback channel

How to minimize the feedback information by allowingpreprocessing in MTs?How to exploit the feedback information with errors?How to design a feedback channel with multiuser access?Multiuser diversity + Beamforming for MIMO/MISO OFDMAEssentially Cross-layer design problems


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Reference

M. Morelli, C.-C. J. Kuo, and M. Pun, Synchronization techniques

for orthogonal frequency division multiple access (ofdma): A

tutorial review, vol. 95(7), pp. 13941427, July 2007.

H. Liu and G. Li, OFDM-Based Broadband Wireless Networks -

Design and Optimization. New Jersey, USA: John Wiley &

Sons, 2005.


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