Uplink Performance Evaluation of CDMA Communication System with RAKE Receiver and Multiple Access Interference Cancellation

doi:10.4236/ijcns.2010.36072

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Int. J. Communications, Network and System Sciences, 2010, 3, 540-547

doi:10.4236/ijcns.2010.36072 Published Online June 2010 (http://www.SciRP.org/journal/ijcns/).

Uplink Performance Evaluation of CDMA Communication

System with RAKE Receiver and Multiple Access

Interference Cancellation

Ayodeji J. Bamisaye, Michael O. Kolawole

Department of Electrical and Electronics Engineering the Federal University of Technology, Akure, Nigeria

E-mail: [email protected] and [email protected]

Received January 26, 2010; revised March 2, 2010; accepted April 10, 2010

Abstract

In CDMA communication systems, all the subscribers share the common channel. The limitation factor on

the system’s capacity is not the bandwidth, but multiuser interference and the near far problem. This paper

models CDMA system from the perspective of mobile radio channels corrupted by additive white noise gen-

erated by multipath and multiple access interferences. The system’s receiver is assisted using different com-

bining diversity techniques. Performance analysis of the system with these detect ion techniques is presented.

The paper demonstrates that combining diversity techniques in the system’s receivers markedly improve the

performance of CDMA systems.

Keywords: CDMA, Multipath Diversity, Multiple Access Interference Cancellation, Rake Receiver, Parallel

Interference Cancellation

1. Introduction

The mobile radio channel plays fundamental limitations

on the performance of wireless communication systems.

The transmission path between the transmitter and the

receiver can vary from simple line-of-sight to one that is

severely obstructed by buildings, mountains, and foliage.

Unlike wired channels th at are stationary and predictable,

radio channels are extremely random and do not offer

easy analysis. Even the speed of motion impacts how

rapidly the signal level fades as mobile terminal moves

in space. Modelling the radio channel has historically

been one of the most difficult parts of mobile radio sys-

tem design, and is typically done in a statistical fashion,

based on measurements made specifically for intended

communication system or spectrum allocation. Code

Division Multiple Access (CDMA) is a multiple access

technology that utilizes direct-sequence spread spectrum

(DS-SS) techniques. With this technology comes a para-

digm shift, including the use orthogonal or nearly or-

thogonal codes (so-called spreading sequences) to

modulate the transmitted bits. Contrary to the conven-

tional frequency division multiple access (FDMA) and

time division multiple access (TDMA) systems where

noise rejection d eals, primarily with out-of-band noise, a

CDMA system concerns mostly with inband noise. This

noise may come from self-jamming (or self-noise), back-

ground noise, man-made noise, inter-modulation, or

noise generated in the receiver [1,2]. If one can reduce

the unwanted in-band noise, such reduction translates

directly into improved performance. Undesired noise

comes from many different sources. This noise may

come from natural or human sources. Naturally occur-

ring noise includes atmospheric disturbances, back-

ground noise, and thermal noise generated in the receiver

itself. Through careful engineering, the effects of many

unwanted signals can be reduced [3]. DS-CDMA is a

multiple access system, where multiple users share a

limited resource, the frequency. Conventional asynchro-

nous DS-CDMA systems allow each user to transmit and

receive independently. Each receiver performs a simple

correlation between the received baseband signal and the

corresponding user’s spreading sequence. In a low-noise

channel with orthogonal spreading sequence,this app-

roach would be optimal. Due to the synchronicity of us-

ers and the need to support numerous users, such ortho-

gonality is impossible, even on a hypothetical AWGN

(additive white Gaussian noise) channel [4]. Thus, sys-

tem performance rendered multiple-access interference

(MAI) limited, and channel utilization is correspo ndingly

low.

This paper m odel s C DM A sy st em fr om t he pers pect ive

A . J. BAMISAYE ET AL.541



of mobile radio channels corrupted by additive white

noise generated by multipath and multiple access inter-

ferences. The system’s receiver is assisted using different

combining diversity techniques. Performance analysis of

the model with different detection techniques will be

presented.

1.1. Mobile Radio Channel Model

Mobile radio channel is one of the most important ele-

ments in the mobile communication systems. When the

signals are transmitted through Mobile radio channel, it

is affected by shadow or large scale fading. Mobile

communication is affected by multipath fading in addi-

tion to shadow fading. Multipath fading is caused by

atmospheric, scattering, and reflection from building and

other object. Multipath channel can be classified as dis-

crete (consisting of resolvable multipath components)

and diffuse (consisting of irresolvable multipath compo-

nents) [5,6]. Consequently, the multipath fading could

affect the transmitted sig nals in two ways: due to disper-

sion (also called time spreading or frequency selectivity),

and due to time variant behaviour of the channel (due to

motion of the receiver or changing environment such as

of foliage or movement of reflectors and scatter). This

means that the impulse response



,ht



of mobile radio

channel is time variant [6,7], and if







has a zero

mean, then the en velope ht,





has a Rayleigh distribu-

tion with its probability density function described by



exp 2

pr 2













(1)

where r is time dependent received signal (i.e.,

()

() ||

rtr e





,  is its arbitrary phase) whose line of

sight (LOS), specular, and diffuse components are as-

sumed bounded in narrowband form, and 2



is the

total power in the multipath signal. In this case the total

power is considered to have zero-mean, amplitude fading.

Otherwise, if the impulse response has a non-zero mean,

then the envelope mobile radio channel would have a

Rician distribution with its probability density function

expressed as:



22 2

exp 2o

prI 2





 















(2)

where 2

is the power of the line-of-sight component,

and o

denotes the zeroth order Bessel function of the

first kind argument (.). The Rayleigh distribution is a

special case of Rician distribution when s = 0; i.e., wher e

the LOS component is negligible.

In most general case, the channel can be modelled as

channel at time (t) to an impulse at time (t-τ). If x(t)

represents the transmitted (or emitted) signal through

noiseless mobile radio channels, the received signal, r(t)

can be expressed as



 

,rthtxtd









 (3)

If the channel information is considered

ch , its distributed

annel impulse response may be expressed as

 



ht t











 (4)

In view of (4) in (3), we write modified channel re-

ceived signal:





rtxt j











 (5)

β(t) is complex amplitude,



j is the path delay, and N

1.2. Rake Receiver

onventional matched filters are single pa th detectors. In

the number of multipath components. In the wideband

channel where the delay-line model had a large number

of taps, not all the multipath components are likely to

fade simultaneously. This may be used as a multipath

diversity to improve the received signal SINR (carrier to

interference plus noise ratio). Rake receiver, for instance,

can be used to mitigate the effect of fading if the trans-

mitted signal bandwidth is larger than the coherence

bandwidth; a practical example is in the wideband-

CDMA (WCDMA).

practice, when the transmitte d signal passes through mo-

bile radio channel, duplicates of the transmitted signal

are generated by reflection, refraction, and diffraction,

and the signal power is distributed in multipath. In

CDMA system, the transmitted signal bandwidth is much

larger than the coherent bandwidth of the channel, in

which case the channel is frequency selective [4,8,9]. For

the frequency-selective channels, the received signals are

multiple copies of the transmitted signals with different

channel delays and fading, combining the multipath

components as multipath diversity. Thus, if one of the

multipath components is attenuated by fading, some oth-

ers may not be and the receiver could use unfaded com-

ponents to make the decision. The idea behind the rake

reception technique is that the signals propagating

through different multipath are received in individual

fingers of the rake receiver and the outputs from these

fingers are then coheren tly co mbined to prov id e the inpu t

signal for the symbol decision. The received signal is

chip matched and sampled at the chip rate. Figure 1,

illustrates the structure of a typical rake receiver in which

*()

i and *,()

(k = 1, 2, ..., K; m = 1, 2, ..., M) rep-

t, resply, the complex conjugate of chip- resenective

channel matched sampled signature sequence of the user

linear time-variant system [2] giving the response of the

A. J. BAMISAYE ET AL.

542

f interest and the complex conjugate estimate of the

n on the transmitted information bit is

mate of the

n on the transmitted information bit is

impulse response.

Then, the decisio

impulse response.

Then, the decisio

sed on the sum of the individual correlator’s outputs.

In our study, the dimension of each correlator equals the

system processing gain, and then the output of each fin-

ger



sed on the sum of the individual correlator’s outputs.

In our study, the dimension of each correlator equals the

system processing gain, and then the output of each fin-

ger



i is given after channel is matched and corre-

latin



for

 

111

PG MK

kmk jk

jmk

icisir i



 1



(where ) (6)

where PG gain,

pled sig

.2.1. Multistage Receivers r detector is the output of

the conventional matched filters receiver for single user k

In the case of multiple K active users, the received sig-

nal in the receiver is

So, the modified output of the co

filter receiver yk for the kth user is

(9)

Expression (9) consists of three terms. The first term is

the desired information which gives the signal of the

1, 2,,mM

is the processing *,()

ciis the complex

conjugate estimate of the channepulse response,

)(

*,is jk is the complex conjugate of chip-matched sam-

nature sequence of the users of interest.

l's im

The input signal of a multiuse

the matched filter bank, or rake receiver. Almost all

modern multiuser detection techniques deal with the out-

put of the matched filters bank and the cross-correlation

information of all users in the system. Expressions (1)

through (6) assumed noiseless cases, which is not valid

in real life situation. If the time-dependent interference

components,



nt , are assumed additive, the output of

can be expressed as:

 

** **

PG PG

kkkkkk

yicisiricisint







(7)

1i



() ()

rtr tnt

 (8)

1k

nventional matched

  

kkkk

yricisi





  

** **

11 1

KPG PG

jkk kk

ji i

cisi cisint

 





 

formation bit (which is exactly what is sought). The

second term is the result of multiple access interference

(MAI), and the last term is due to noise. The second term

typically dominates the noise so that one would like to

remove its influence. Its influence is felt through the

cross-correlation between the chip sequences and the

device-powers of users. If o ne knew the cross-correlations

and the powers, then one would attempt to cancel the

r(i)

)(

*is

)(

*is

)(

*is

c)(

*1, i

k )(

*2, ick)(

*,ic Mk

T c

Correlator T

o(.)

Finger1

Correlator T

o(.)

Finger 2

Correlator T

o(.)

Finger M

y(i)

Figure 1. Rake Receiver with M fingers.

y1 y2 yM

A . J. BAMISAYE ET AL.543

front end, a SIC receiver (ordecorrelator) can be used

on and Results

erformed for different

nce cancellation);

ting Detector and

is clearly stated. It is assumed that the system

ta is obtained by passing the soft

Simulations were performed for 10 active users sending

to 100total of 10000 symbols. The

in cance-

lli

Similar parameters used in 1.3.1 are used in this analysis

In add are updated ran-

ectively, while other

performance is the

effect of one user upon another. This is, in fact, the

intuitive motivation for interference cancellation scheme.

The difference between multistage receivers and suc-

cesssive interference canceller (SIC) receivers is that

stead of using previous bit decisions to cancel interfer-

eence from desired user’s signal as in SIC, tentative de-

cisions on each user are used to improve signal quality

[10]. Receiver structure is called multistage, since when

decisions are made, they can be used to either make a

final decision on data or to enhance the signal through

cancellation. Reference signals are based on initial bit

estimates, which are then subtracted from received signal

to produce a cleaned spread signal for next stage. Since

all signals are detected at each stage simultaneously,

multistage receivers are also called parallel interference

cancellers (PIC). A two-user multistage receiver is

shown in Figure 2. The p-stage receiver outputs are



1,pp

, where 1, 2,p.

Instead of a conventional (matched filter) receiver

1]. Performance of PIC is best when received signal

powers are equal. Capacity of the system is limited by

hardware.

1.3. Simulati

Performance evaluations were p

scenarios using:

1) Conventional matched filters receiver with PIC

(parallel interfere

2) Rake receiver with PIC;

3) Rake receiver with Decorrela

MSE; and

4) Conventional matched filters receiver and rake re-

ceiver.

For each analysis, the number of users’ symbols tran-

smitted

es unencoded BPSK signal, as well as no pulse-

shaping filter. Each transmitted MS within each loop

sends a block of data bits of known length. The input of

MUD (multi user detection) is the soft decision of either

rake receiver or conventional matched filters. In the

simulation, the sub-optimum linear MUD decorrelating

detector, linear minimum mean squared error (LMMSE)

detector, and nonlinear sub-optimum PIC were built for

the multishot model.

In relation to the decision operation, the hard decision

output of received da

cision output through the design circuit, which repre-

sents any sign function for BPSK. Also, we make the

number of channel paths P equal the number of fingers M

to make the rake receiver simpler in structure. In a less

equivalent case, that is, when M < P or M > P, the system

performance degrades. Therefore, the matched case pro-

vides the optimally achievable performance reference.

1.3.1. Performance of Conventional Matched Filters

Receiver with PIC

10 symbols within each loop. The maximum loop equals

. The users send a

data are then spread by Walsh code and scrambled by

Gold code with processing gain of 32. The channel pa-

rameters are updated randomly in each loop.

Simulation results are shown in Figure 3, which de-

monstrates progressive improvement in the system per-

formance with diversity combining techniques

ng multiple access interferences.

1.3.2. Performance of Conventional Matched Filters

Receiver and Rake Receiver

except the processing gain, PG, which is increased to 64.

ition, the channel parameters

domly in each loop and the number of paths for each user

changes randomly over (2-6). Two tests were carried out

in this subsection: (i) to investigate the effect of rake

receiver in the system for a single user and (ii) to inves-

tigate the effect of rake receiver and conventional

(matched filter) receiver with a range of channel paths.

Figure 4 shows the performance with rake receiver

and without rake receiver for a single user. In the re-

ceiver, ‘equal gain combining’ method is used in rake

e analysis demonstrates that lowering the SNR does

not improve the system when SNR equals 20 dB, the

BER is 10–2.9 and 10–1.9 respectively for conventional

matched filter receiver and rake receiver. In contrast,

improvement in system performance can be achieved by

increasing SNR in both sche m e s.

In the case of test (ii), an AGWN is assumed in the

channel paths. The number of users and the processing

gain are decreased to 6 and 8 resp

rameters are the same as previous simulations. The

channel parameters are updated randomly in each loop,

and the simulation computes for the different values of

channel path, as shown in Figure 5.

Figure 5 shows the performance of the rake and con-

ventional receivers for a number of multipath scenarios.

In the case of one path, the system

me for matched filter (MF) and rake receiver. But in

the case of multipaths; for example, (4-path) the system

performance with conventional matched filter degrades,

whereas the system performance with rake receiver im-

proves. Also, for the case of (7-path) the performance of

MF becomes very poor, but improves markedly with

rake receiver. As a result, the system performance can be

deduced as increasing when diversity scheme is em-

ployed. Under Gaussian noise as interferer, the system

performance improves with in creasing channel path with

the rake receiver, which might not be optimal in real life

situation.

A. J. BAMISAYE ET AL.

544

Delay +Conventional

receiver

Decision device

Sampled signal

generator

Sampled signal

generator

Decision device

Delay +Conventional

receiver

yk1

+ -





yk1









1()yt 1()

1k





2()

21()



Figure 2. A two-user multistage receiver.

-20 -10 010 20 30 40 50 60

10-3

10-2

10-1

100

MF DD

MF MMSE

P IC - S tage1

P IC - S tage2

P IC - S tage3

Bit Error Rate

Figure 3. CDMA system performance evaluation using conventional matched filter (MF), with different diversity techniques:

decorrelating detector (DD), m mean squared error (MMSE) , and th ree-stage parallel internce cancellation (PIC). minimu fere

SNR (dB)

Figure 4. System performance of Rake receiver and conventional matched filters’ receiver.

A . J. BAMISAYE ET AL.

545

-20 -10 010 20 30 40

-2

-1

S y st em performance

Bit Error Rate

1 pat h : conve nt i onal m at ched fil t er

1 path :RA K E rec ei ver

4 path :c onvent i onal matc hed fil ter

4 path :RA K E rec ei ver

7 pat h : conve nt i onal m at ched fil t er

7 path :RA K E rec ei ver

SNR (dB )

Figure 5. System performance of Rake receiver and conventional matched filters’ receiver with different number of channel

paths.

1.3.3. Performance of RAKE Receiver with

Decorrelating Detec tor and MMSE

Similar parameters used in 1.3.1 are used in this analysis.

In addition, the channel parameters are updated ran-

domly in each loop, and the number of paths for each user

changes randomly between 2 and 5. Figure 6 clearly

shows the importance of multiuser detection (MUD). Teh

figure shows that for one path, marginal improve- ment in

system performance is gained whether conventional

matched filters receivers are used or in combination with

decorrelating detector (DD) or with minimum mean

squared error (MMSE) schemes. Note that the correlation

matrix only contains the information of multiple access

interferences in the first path and treated the other paths

as AWGN. On the otherd, system performance im-

at of [11].

1.3.4.ith Parallel

performance improved by using rake receiver instead of

conventional matched filters.

1.3.5. Perf or mance with Var iable Processing Gain

In this simulation, 8 active users send 10 symbols re-

spectively within each loop. The maximum loop is equal

to 100, totalling 8000 symbols sent by the users. The

data are then spread by Walsh code and scrambled by

Gold code with performance gains of 16 and 64. The

channel parameters are updated randomly in each loop,

and the number of channel path change randomly be-

tween 2 and 4. The received signal is processed with rake

and conventional matched filters respectively. Decorre-

lating detector is employed to cancel the multiple access

interference. Figure 8 indicates the processing gain in-

strate that large processing gains translate to high per-

CDMA system from the per-

pective of mobile radio channels corrupted by additive

interfver was assisted with

han

proves markedly using rake receiver and MUD when

taking the multipath into account; a finding consistent

ith th

fluence to the system performance. The results demon-

Performance of RAKE Receiver w

Interference Cancellation

For this simulation, 10 active users send 10 symbols re-

spectively within each loop. The maximum loop is equal

to 150, with a total of 15000 symbols sent. The data are

then spread by Walsh code and scrambled by Gold code

with performance gains, PGs, of 16 and 64. The chann el

parameters are updated randomly in each loop, and the

number of channel path change randomly between 2 and

4. The received signal is processed with rake and con-

ventional matched filter respectively. Three-stage paral-

lel interference cancellation is employed to cancel the

multiple access interference. As shown in Figure 7, the

formance gain of the system.

1.4. Conclusions

This paper has modelled a

white noise generated by multipath and multiple access

erences. The system’s recei

different combining diversity schemes.The simulation is

focused on the most important factors that will influence

the performance of the CDMA systems using multi user

detection method and interference cancellations scheme.

Performance analysis of the system using the different

detection techniques was presented. The paper estab-

Lished that diversity-combining techniques markedly im-

A. J. BAMISAYE ET AL.

546

-20 -1001020 304050 60

-4

-3

-2

-1

Sys t em pe

rformance

conventional receiver

RAKE receiver

conventio nal receiver with DD

RAKE receiver with DD

conventio nal receiver with MMS E

AKE receiver with MMSE

Ra t

B i t Error

imum mean squared error (MMSE).

(dB)

Figure 6. System performan ce of Rak e receiver with decorrela

ting detector (DD) and min

-20 -10 010 20 3040

-3

-2

-1

E rr or ra te vs SNR

B i t E rror Rate

conventional receiver

RAKE receiver

MF:PIC - Stage1

MF:PIC - Stage2

MF:PIC - Stage3

RAKE:PIC - Stage1

RAKE:PIC - Stage2

RAKE:PIC - Stage3

SNR ( dB)

Figure 7. The system performance of RAKE receiver with three-stage parallel interference cancellation (PIC).

-20 -10 01020 30 40 50 60

-4

-3

-2

-1

S y st em pe rformance

S NR (in dB)

B i t Error Rate

conventional receiver(PG=16)

RAKE receiver(PG=16)

conventional receiver with DD(PG=16)

RAKE receiver with (PG= 16)

conventional receiver(PG=64)

RAKE receiver(PG=64)

conventional receiver with DD(PG=64)

RAKE receiver with (PG= 64)

Figure 8. System performance of RAKE receiver with differen

SNR (dB)t.

A. J. BAMISAYE ET AL.547

prove t

portant factor in reducing the multiple access interfere-

ence, is the processing gain which the model employed.

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