Coverage of WCDMA Network Using Different Modulation Techniques with Soft and Hard Decision Decoder

7/27/2019 Coverage of WCDMA Network Using Different Modulation Techniques with Soft and Hard Decision Decoder

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International journal of Computer Networking and Communication (IJCNAC)Vol. 1, No. 1(August 2013) 71

www.arpublication.org

Coverage of WCDMA Network Using Different

Modulation Techniques with Soft and Hard

Decision DecoderJ.Jayadharini1, P.Saveeda2, Prof.K.Ayyappan3

1Department of Information Technology, Madras Institute of Technology, Chennai, India

[email protected] of ECE, Rajiv Gandhi College of Engineering & Technology, Pondicherry, India

[email protected] of ECE, Rajiv Gandhi College of Engineering & Technology, Pondicherry, India

[email protected]

AbstractThe wideband code division multiple access (WCDMA) based 3G cellular mobile

wireless networks are expected to provide a diverse range of multimedia services to

mobile users with guaranteed quality of service (QoS).To serve diverse quality of service

requirements of these networks it necessitates new radio resource management strategies

for effective util ization of network resources with coding schemes. In this paper coverage

area for voice traffic and with different modulation techniques, coding schemes and

decision decoder are discussed. These discussions are to improve the coverage area in

the mobile communication system. This paper is mainly focuses on coverage area of

WCDMA system using link budget calculation with different modulation, coding schemes

and decision decoder. Simulation results demonstrate coverage extension for voice

service with different modulation,coding scheme, soft and hard decision decoder using

appropriate Bit error rate (BER) to maintain QoS of the voice.

Keywords: Link budget, WCDMA, Bit rate, Traffic, Coverage area, Convolutional code,Decoder.

1. INTRODUCTIONTelecommunication is the assisted transmission of signals over a distance for the purpose of

communication. It is the technology of transferring information over a distance. GSM and CDMA

are the technologies in telecommunication. This paper is mainly focuses on the link budget

calculation of WCDMA system in terms of emission and coverage capabilities. The application of

code division multiple access (CDMA) technology was introduced in cellular systems in the early

1990s with the development and commercialization of the IS-95 standard. The CDMAtechnology has evolved from IS-95 to CDMA 2000 [1-5].

All 2G-CDMA (IS95) based networks have migrated to cdma2000-1X technology, primarily

based on the IS2000. The only difference between 2G-CDMA (IS95) and CDMA2000 is the

number of channel element present in each system. The operation and function of IS95 and

CDMA2000 are same. The name cdma2000 actually denotes a family of standards that represent


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the successive, evolutionary stages of the underlying technology. The CDMA standard allows up

to 61 simultaneous users in one 1.2288 MHz channel.

It is a part of the ITU IMT-2000 family of 3G Standards. It was also known as IMT-2000 direct

spread. And it is derived from CDMA. Its specifications originated from 3GPP Radio Access

Network (RAN) group. WCDMA uses one 5MHZ band for transmitting both voice and data. It is

used by UMTS and NTT DoCoMos FOMA network. It facilitates high data rates to wirelessdevices. It is a spread spectrum modulation technique whose channels have bandwidth much

larger than the maximum data rate instead of using a single dedicated bandwidth for each

connection [6-10].

W-CDMA can support mobile/portable voice, images, data, and video communications at up to

2 Mbpsfor local area access or 384 Kbps for wide area access. The input signals are digitized andtransmitted in coded, spread-spectrum mode over a broad range of frequencies. A 5MHz-wide

carrier is used, compared with 200 KHz-wide carrier for narrowband CDMA [11].

2. MODELOKUMURA-HATA PROPAGATIONOkumura developed an empirical model that is derived from extensive radio propagation

studies in Tokyo. It is represented by means of curves with which is applicable for urban areas.

For other terrain, Okumura has provided correction factors for three types of terrain:

Open Area: Corresponds to a rural, desert type of terrain. Quasi Open area: Corresponds to rural, countryside kind of terrain. Suburban area.

HATA model is the most widely used radio frequency propagation model for predicting thebehaviour of cellular transmission. HATA Model predicts the total path loss along a link of

terrestrial microwave or other type of cellular communications. This model has three different

path loss models for different environments namely urban, sub-urban and rural. This model is

suited for both point-to-point and broadcast transmissions and it is based on extensive empirical

measurements taken.

For Urban environment,

(1)

For Sub-urban environment,

(2)

For Rural environment,

(3)

Where f is frequency

ht is height of the transmitter

hr is height of the receiver

d is the coverage distance


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3. MODULATIONTECHNIQUE3.1QPSK

The most commonly preferred modulation techniques in WCDMA technology are QPSK and

16QAM. Here QPSK has discussed. QPSK is a form of PSK where 4 different angles separated

by 90 is used. In QPSK, data are transmitted by modulating their carriers. 2 bits are modulatedsimultaneously by selecting a carrier phase shifts among the available four (0, 90, 180, 270

).

There are two carriers (In-phase, Quadrature phase). The 4 states of a 2-bit binary code is denotedby changing the phase of In-phase carrier from 0 to 180 and changing phase of quadrature phase

from 90 and 270.QPSK is an M-ary encoding scheme where N=2 and M=4 (hence, the name

quaternary meaning 4). It is widely used in CDMA, Cable modems, Video Conferencing

[12,13].

For transmitting data, OQPSK uses four distinct phases. Offset quadrature phase-shift key is a

type of phase-shift keying modulation which uses 4 distinct values of the phase for transmission.

By considering 4 values of the phase (two bits) at a time to construct a QPSK symbol can allowthe phase of the signal to jump by as much as 180 at a time. This produces large amplitude

fluctuations in the signal; an undesirable quality in communication systems. By offsetting thetiming of the odd and even bits by one bit-period, or half a symbol-period, the in-phase and

quadrature components will never change at the same time. This will limit the phase-shift to no

more than 90 at a time which results in lower amplitude fluctuations than non-offset QPSK [14-16].Advantage:

Maximum phase change is /2. The envelop is relatively remain constant. Power-efficient. Non-linear power amplification can be used without too much distortion in bandwidth.

3.216QAMQuadrature Amplitude Modulation is used in communication. 16- QAM is a variant of QAM.

In QAM, the constellation points are usually arranged in a square grid with equal vertical and

horizontal spacing. It is the first considered rectangular QAM constellation. Error rate of 8-QAM

0.5 dB better than 16-QAM but its data rate is only three-quarters that of 16-QAM. It has 4 bits

per symbol and its symbol rate is bit rate. It is used for digital terrestrial television using DVB -

Digital Video Broadcasting in UK. It meets the users high throughput needs and so it is highly

used in services like Voice over IP and P2P services [17].

4. CODINGSCHEMES4.1

BLOCK CODE

Block codes comprise the large and important family of error-correcting codes that encode data

in blocks. Error-correcting codes are used to reliably transmit digital data over unreliable

communication channels subject to channel noise. When a sender wants to transmit a possibly

very long data stream using a block code, the sender breaks the stream up into pieces of some

fixed size. Each such piece is called message and the procedure given by the block code encodes

each message individually into a codeword, also called a block in the context of block codes. The

performance and success of the overall transmission depends on the parameters of the channel


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and the block code. Block code is code in which extra parity bits are inserted periodically. The

parity bits carry no extra information but they help us to detect bit errors.

4.2CONVOLUTIONAL CODEA convolutional code is a type of error-correcting code in which each m-bit information symbol

to be encoded is transformed into an n-bit symbol, where m/n is the code rate and thetransformation is a function of the last k information symbols, where k is the constraint length of

the code. Convolutional codes are used extensively in numerous applications in order to achieve

reliable data transfer, including digital video, radio, mobile communication and satellite

communication

4.3DECISION DECODERThe hard decision technique can detect any number of errors which are less than or Equal to the

correction capacity of the code. However, for three or more errors in the case of CC (2, 1, 3)

encoder, the decoded sequence is generally incorrect. The soft decision technique decodes

correctly any corrupted sequence with one or 2 errors independently of the quantification levels

attributed to the symbols of a given received sequence. For three or more errors, this techniquedetects these errors if they have a low quantification levels and the non corrupted bits have a high

confidence. The noise corrupting the transmitted signal is generally low compared with the signal

and cannot reach the signal level. Therefore the confidences of the error bits are generally low

and the soft decision technique can detect them. As a conclusion, it can be said that the soft

decision technique is powerful compared with the hard decision technique and is suitable for

AWGN channels.

A soft-decision decoder is a class of algorithm used to decode data that has been encoded with

an error correcting code. Whereas a hard-decision decoder operates on data that take on a fixed

set of possible values typically 0 or 1 in a binary code, the inputs to a soft-decision decoder may

take on a whole range of values in-between. This extra information indicates the reliability of

each input data point, and is used to form better estimates of the original data. Therefore, a soft-decision decoder will typically perform better in the presence of corrupted data than its hard-

decision counterpart.

5. PERFORMANCEANALYSISThe objective of this simulation is to analyse the coverage extension for voice service with

different coding scheme, soft and hard decision decoder using appropriate BER to maintain QoS

of the voice The simulation parameters which are used are shown in Table 5.1.

Parameters Values

Bit Rate 12.2kbps

Transmitter power 20 WTx Antenna gain 17 dBi

Tx Body loss 2 dB

Tx cable loss 0 dB

Tx EIRP 40dBm

Interference Margin 6.02 dB

Rx Cable loss 0 dB

Rx Body loss 2 dB


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Required Signal Power -112.116 dBm

Soft handover gain 1 dB

Shadow Fading Margin 7.5 dB

Carrier frequency 2100 MHz

BS Antenna Height 25m

MS Antenna Height 1.5m

Table-5.1.Parameters for Link Budget Calculation

5.1Coverage Area for different Eb/N0 in QPSK Modulation technique with Convolutional& Block codes with Decision Decoders.

The table 5.2 shows the different values of Eb/N0 for different coding scheme with hard and soft decision

decoder for the three different preferable Bit Error Rates which are denoted as BER 1, BER 2 and BER 3.

BER

Eb/N0

Convolutional Block

Hard Soft Hard Soft

10-3 (BER 1) 5.03 dB 2.76 dB 5.87 dB 4.43 dB

10-4

(BER 2) 5.82 dB 3.55 dB 7.35 dB 5.82 dB10-5 (BER 3) 6.56 dB 4.15 dB 8.42 dB 6.84 dB

Table 5.2: Eb/N0 Values for different coding scheme with Hard & Soft decision decoders

Fig. 5.1 Coverage Area using Convolutional Code Hard Decision -QPSK

The Fig.5.1 shows the coverage area for QPSK modulation technique using convolutional coding with

hard decision decoder for preferable BER namely BER1, BER2 and BER3 which have the coverage

distance of 2.04km, 1.94km and 1.85km respectively. BER1 has the more coverage distance as compared

to the other BERs.


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Fig. 5.2 Coverage Area using Convolutionaal Code Soft Decision-QPSK

Fig.5.2 shows the coverage area for QPSK using convolutional coding with soft decision decoder for

BER1, BER2 and BER3 which cover the distance of 2.36km, 2.24km and 2.16km. Similarly Fig.5.3 and

Fig.5.4 describe the coverage area for QPSKmodulation technique using block code with hard decision

decoder which covers the distance of 1.93km, 1.76km and 1.64km for the BER1, BER2 and BER3 and

with soft decision decoder, the BER1, BER2 and BER3 have its coverage area of 2.12km, 1.94km and

1.81km respectively.

Fig. 5.3 Coverage Area using Block Code Hard Decision- QPSK


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Fig. 5.4 Coverage Area using Block Code Soft Decision-QPSK

5.2Coverage Area for different Eb/N0 in 16 QAM Modulation techniques withConvolutional & Block codes with Decision Decoders.

The table 5.3 contains the different Eb/N0 values for different preferable Bit Error Rates for different

coding schemes (Convolutional & Block) with hard decision decoder.

BER

Eb/N0 (dB)

Convolutional Block

Hard Hard10-3 (BER 1) 8.33 dB 9.16 dB

10-4 (BER 2) 9.21 dB 10.79 dB

10-5 (BER 3) 10.04 dB 11.99 dB

Table 5.3: Eb/N0 Values for different coding schemes with Hard decision decoder..

Fig. 5.5 Coverage Area using Convolutional Code with Hard Decision -16 QAM


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Fig. 5.6 Coverage Area using Block Code with Hard Decision-16 QAM

The Fig.5.5 and 5.6 show the coverage area for 16 QAM modulation technique using convolutional withhard decision decoder which has the greater coverage distance of 1.65km for BER1 and block code with

the coverage areas of 1.56km, 1.41km and 1.30km for different bit error rates according to the Quality of

service.

5.3Coverage Area for different Modulation Technique with different Coding Scheme withDecision Decoder

Fig.5.7 Coverage Area for QPSK and 16 QAM


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Fig.5.7 explains the coverage area for the different modulation techniques using different coding scheme

with the hard decision. From the above bar graph, it is clearly shown that the QPSK convolutional code

with hard decision decoder has more coverage distance 2.04km than the other modulation technique with

the hard decision of convolutional code and block code.

6. CONCLUSIONIn this paper, the coverage area of WCDMA network for different modulation technique such as QPSK

and 16 QAM with Block and convolutional coding schemes are calculated using soft and hard decision

decoder. The WCDMA network coverage area is enhanced for the QPSK modulation technique using

convolutional coding scheme with hard decision decoder compared to the remaining schemes.

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Authors

J.JAYADHARINI is a Student and pursuing her Bachelor Degree in Information

Technology in Madras Institute of Technology, Chennai, India. She is member of

YRC. She is Head of Web team in CSMIT (2013-14) of MIT. She won prizes in

inter college technical competitions.

P. SAVEEDA received the degree in Electronics and communication from Rajiv

Gandhi College of Engineering and Technology, Pondicherry, India in 2013. Her

area of interest is wireless communication and doing project in cellular mobile

communication. She has published 5 papers in international journals in the same

area. She is member of IETE.

Prof.K.AYYAPPAN received the Bachelors Degree in Electronics andCommunication Engineering from Bharathidasan University in 1989. He completed

his Masters degree in Power Systems from Annamalai University in 1991. He is

Professor in ECE department of Rajiv Gandhi College of Engineering and

Technology, Pondicherry, India. He is pursuing research in the area of wireless

communication. He has published 20 papers in international journals and

conferences in the same area. He is member of FIETE,ISTE, ACEEE,IDES,SDIWC

and IACSIT.

Documents

Coverage of WCDMA Network Using Different Modulation Techniques with Soft and Hard Decision Decoder