The 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 utilization 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.

1. International journal of Computer Networking and Communication (IJCNAC)Vol. 1, No. 1(August 2013) 71
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Coverage of WCDMA Network Using Different
Modulation Techniques with Soft and Hard
Decision Decoder
J.Jayadharini1
, P.Saveeda2
, Prof.K.Ayyappan3
1
Department of Information Technology, Madras Institute of Technology, Chennai, India
1
jjdharini@gmail.com
2
Department of ECE, Rajiv Gandhi College of Engineering & Technology, Pondicherry, India
2
savee197@gmail.com
3
Department of ECE, Rajiv Gandhi College of Engineering & Technology, Pondicherry, India
3
aaa_rgcet@yahoo.co.in
Abstract
The 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 utilization 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. INTRODUCTION
Telecommunication 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 CDMA
technology 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 DoCoMo’s FOMA network. It facilitates high data rates to wireless
devices. 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 and
transmitted 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. MODEL OKUMURA-HATA PROPAGATION
Okumura 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 the
behaviour 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. MODULATION TECHNIQUE
3.1 QPSK
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 modulated
simultaneously 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 denoted
by 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 allow
the 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 the
timing 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 π/2.
• The envelop is relatively remain constant.
• Power-efficient.
• Non-linear power amplification can be used without too much distortion in bandwidth.
3.2 16QAM
Quadrature 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 ¼ 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. CODING SCHEMES
4.1 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.
4.2 CONVOLUTIONAL CODE
A 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 the
transformation 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
4.3 DECISION DECODER
The 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 technique
detects 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. PERFORMANCE ANALYSIS
The 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 W
Tx 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
5.1 Coverage 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 dB
10-5
(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 QPSK modulation 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
5.2 Coverage Area for different Eb/N0 in 16 QAM Modulation techniques with
Convolutional & 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 Hard
10-3
(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 with
hard 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.
5.3 Coverage Area for different Modulation Technique with different Coding Scheme with
Decision 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. CONCLUSION
In 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 and
Communication 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.