Application of diversity techniques for multi user idma communication system

Network and Complex Systems www.iiste.org
ISSN 2224-610X (Paper) ISSN 2225-0603 (Online)
Vol.3, No.2, 2013-National Conference on Emerging Trends in Electrical, Instrumentation & Communication Engineering
26
Application of Diversity Techniques for Multi User IDMA
Communication System
Aasheesh Shukla,Rajat Sapra,Vishal Goyal
Department of Electronics & Communication Engineering, GLA University, Mathura, India
E-mail: aasheeshshukla@gmail.com , sapra.glaitm@gmail.com
.M. Shukla
Department of Electronics & Communication Engineering, Harcourt Butler Technological Institute, Kanpur,
India
E-mail: manojs@hbti.ac.in
Abstract
In wireless communication, fading problem is mitigated with help of diversity techniques. This paper presents
Maximal Ratio Combining (MRC) diversity approach to uproot the fading problem in interleave-division
multiple-access (IDMA) scheme. The approach explains receiver diversity as well as transmits diversity analysis
as 1:2 and 2:1 antenna system in fading environment, no. of antennas can be increased to improve diversity order.
Random interleaver as well tree based interleaver has been taken for study. Significant improvements in
performance of IDMA communication is observed with application of diversity techniques.
Keywords: Random Interleaver, Tree Based Interleaver, MRC diversity, IDMA
1. Introduction
The goal for the next generation mobile communications system is to seamlessly provide a wide variety of
communication services to anybody, anywhere, anytime such as high voice quality, higher data rates etc. The
technology needed to tackle the challenges to make these services available is popularly known as the Third
Generation (3G) Cellular Systems using multiuser detection [1]. The fundamental phenomenon which makes
reliable communication difficult is time varying multipath fading, which is major impairment in any wireless
communication system. The performance improvement is very difficult in such situation
Theoretically, improvement in signal to noise ratio may be achieved by providing higher transmit power or
additional bandwidth which are not feasible solution as they are contrary to the requirements of next generation
wireless communication [2]. On the other hand, the problem of fading may be handled with suitable diversity
technique without expanding communication resources easily.
In most wireless channels, antenna diversity is a practical, effective and widely used technique for reducing the
effect of multipath fading. The maximal ratio combining (MRC) diversity technique, is implemented with
interleave-division multiple-access (IDMA) scheme, as MRC is performed well in comparison with selection or
equal gain combining.[3]-[5]. The IDMA scheme is known as advanced version of CDMA, which inherits many
advantages from CDMA such as dynamic channel sharing, mitigation of cross-cell interferences, asynchronous
transmission, ease of cell planning, and robustness against fading. It also allows a low complexity multiple user
detection (MUD) techniques [7] (CBC detection) applicable to systems with large numbers of users in multi-path
channels.
The objective of this paper is to use MRC diversity in IDMA communication system to reduce the effect of
fading. The study of transmit as well as receiver diversity is taken separately, because both have their own
application area [2]. The paper is organized as follows. Concept of IDMA is introduced in section 2. Section 3
deals with classical MRRC diversity approach used with IDMA. In section 4 transmit diversity is discussed with
IDMA. Performance analysis is provided in section 5. Finally conclusions are presented in section 6.
2. IDMA Scheme
2.1 IDMA Mechanism
The performance of conventional code-division multiple-access (CDMA) systems [1] is mainly limited by
multiple access interference (MAI), as well as intersymbol interference (ISI). Also, the complexity of CDMA
multi-user detection has always been a serious problem for researchers all over the world. The problem can be
visualized from the angle of computational cost as well complexity of multi-user detection algorithms in CDMA
systems. The use of user-specific signature sequences is a characteristic feature for a conventional CDMA
system. The possibility of employing interleaving for user separation in CDMA systems is briefly inducted in [1]
but the receiver complexity is considered as a main problem. In interleave-division multiple-access (IDMA)
scheme, users are distinguished by user specific chip-level interleavers instead of signatures as in a conventional
CDMA system. The scheme considered is a special case of CDMA in which bandwidth expansion is entirely
performed by low-rate coding. This scheme allows a low complexity multiple user detection techniques

27
applicable to systems with large numbers of users in multipath channels in addition to other advantages.
In CDMA scheme, signature sequences are used for user separation while in IDMA scheme, every user is
separated with user-specific interleavers, which are orthogonal in nature. The block diagram of IDMA scheme is
shown in figure 1 for K users. The principle of iterative multi user detection (MUD) which is a promising
technique for multiple access problems (MAI) is also illustrated in the lower part of Fig. 1. The turbo processor
involves elementary signal estimator block (ESEB) and a bank of K decoders (SDECs). The ESEB partially
resolves MAI without considering FEC coding. The outputs of the ESEB are then passed to the SDECs for
further refinement using the FEC coding constraint through de-interleaving block. The SDECs outputs are fed
back to the ESEB to improve its estimates in the next iteration with proper user specific interleaving. This
iterative procedure is repeated a preset number of times (or terminated if a certain stopping criterion is fulfilled).
After the final iteration, the SDECs produce hard decisions on the information bits [8]-[11].
The complexity involved (mainly for solving a size KxK correlation matrix) is O (K2
) per user by the well-
known iterative minimum mean square error (MMSE) technique in CDMA, while in IDMA, it is independent of
user. This can be a major benefit when K is large [12].
2.1 Scheme Model
Here, we consider an IDMA system [1], shown in Figure 1, with K simultaneous users using a single path
channel. At the transmitter, a N-length input data sequence d k = [d k (1), ………, d k (i) , … d k (N)]T
of user k is
encoded into chips ck= [c k (1), ………, c k (j) , … c k (J) ]T
based on low rate code C, where J is the Chip length.
The chips c k is interleaved by a chip level interleaver ‘Πk ’, producing a transmitted chip sequence x k = [x k
(1), … x k (j) , … x k (J) ]T
. After transmitting through the channel, the bits are seen at the receiver side as r = [r k
(1), ……,r k (j) , … r k (J) ]T
. The Channel opted is additive white Gaussian noise (AWGN) channel, for
simulation purpose.
In receiver section, after chip matched filtering, the received signal form the K users can be written as
1
( ) ( ) ( ), 1, 2,....... .
K
k k
k
r j h x j n j j J
=
= + =∑ (1)
Where h k is the channel coefficient for
th
k user and { ( )n j } are the samples of an additive white Gaussian
noise (AWGN) process with mean as zero and variance σ 2 =
N0 / 2. An assumption is made that {h k} are known
priori at the receiver.
The receiver consists of an elementary signal estimator block (ESEB) and a bank of K single user a posteriori
probability (APP) decoders (SDECs), operating in an iterative manner. The modulation technique used for
simulation is binary phase shift keying (BPSK) signaling. The outputs of the ESEB and SDECs are extrinsic log-
likelihood ratios (LLRs) about {x k} defined as
( / ( ) 1)
( ( )) log , , .
( / ( ) 1)
k
k
k
p y x j
e x j k j
p y x j
 = +
= ∀ 
= − 
(2)
Figure 1. Transmitter and Receiver structures of IDMA scheme with K simultaneous users.
These LLRs are further distinguished by the subscripts i.e., ( ( ))ESEB ke x j and ( ( ))SDEC ke x j , depending upon
whether they are generated by ESEB or SDECs.
Due to the use random interleavers {Π k}, the ESEB operation can be carried out in a chip-by-chip manner, with
only one sample r(j) used at a time. So, rewriting (2) as

28
( ) ( ) ( )k k kr j h x j jζ= + (3)
where
' '
'
( ) ( ) ( ) ( ) ( )k k k k k
k k
j r j h x j h x j n jζ
≠
= − = +∑ (4)
is the distortion in r( j) with respect to user-k. ( )k jξ is the distortion (including interference-plus-noise) in
received signal with respect to user-k.
A brief description of CBC algorithm [1] used in IDMA, has been presented in [3]. The operations of ESEB and
APP decoding are carried out user-by-user.
The outputs of the ESEB as extrinsic log-likelihood ratios (LLRs) is given as,
The LLR output of SDEC is given as,
Now, these steps are repeated depending on no. of iterations and users.
3. RECIEVER DIVERSITY ANALYSIS FOR IDMA
The block diagram of maximal ratio combining (MRC) diversity with IDMA scheme is shown in figure 2. In this
method, the diversity branches are weighted for maximum SNR. As shown in block diagram in figure 2, kd is
data of kth user, after encoding and spreading the data is randomly interleaved and termed as ‘chips’. Now this
chip Signal kx is sent from the transmit antenna, which will propagate from both the channel.
If we consider 1 transmit and 2 receive antenna, then channel between transmit antenna and the first received
antenna is h0 and between the transmit antenna and second receive antenna one is denoted by h1. The channel can
be modeled having magnitude and phase response. So,
h0 = α 0
0i
eθ
h1 =α 1
1i
eθ
(5)
Noise can be added at both the receiver. The resulting received signals are
R0 = h0xk + n0
R1 = h1xk + n1 (6)
Where, n0 and n1 represents the noise and interference at both the receiver separately.
Now the Receiver combining scheme for two branches MRRC can be written as
Χ K=h0
∗
R0 + h1
∗
R1 (7)
Now this output of maximal ratio combiner can fed to the detector for the proper estimation of transmitted signal
xk.
Figure 2. IDMA with proposed two branches MRRC diversity scheme for kth
user
2
( ) ( ( )) ( ( ))
( ( )) 2 .
( ) ( ( ))
k k
ESEB k k
j k k
r j E r j h E x j
e x j h
Var r h Var x j
− +
=
−
1
( ( ( ))) ( ( ( )))
S
SDEC k ESEB k
j
e x j e x jπ π
=
= ∑ 1,...,j S=

29
4. TRANSMIT DIVERSITY ANALYSIS FOR IDMA
In this section transmit diversity is discussed with IDMA communication system; figure 3 is showing the
arrangements for kth user. After encoding and spreading the data is interleaved then sent by two transmit antenna.
If two transmit antenna and one receive antenna system is used, then channel between first transmit antenna (t0)
and receiver antenna is h0 and between second transmit antenna (t1) is h1. So, the channel can be modeled like:
= ( )
= ( ) (8)
At a given symbol period two signals are simultaneously transmitted from two antennas. The signal transmitted
from antenna zero is S0 and antenna one is S1. During next symbol period conjugate of (-S1) is transmitted from
antenna zero and conjugate signal S0 is transmitted from antenna one, i.e. transmitted symbols are space time
encoded. Now the received signal can be written as
= ( ) = ℎ + ℎ +
= ( + ) = −ℎ ∗
+ ℎ ∗
+ (9)
These two signals will be received by the same antenna after a delay of T (Symbol period).
0 = ℎ∗
+ ℎ ∗
1 = ℎ∗
− ℎ ∗
(10)
Solving equations (8), (9) and (10), we can write
0 = ( + ) + ℎ∗
+ ℎ ∗
1 = ( + ) + ℎ ∗
+ ℎ∗
(11)
Now finally these two signals fed in to the CBC detection based IDMA detector.
Figure 3. IDMA with proposed transmit diversity scheme for kth
user
5. PERFORMANCE ANALYSIS
For simplicity, IDMA system with BPSK signaling is assumed with uniform repetitive coding and spread length
16, for all users along with 15 iterations.
The interleavers used in simulations are random interleaver (RI) [3] and tree based interleaver (TBI) [15].

30
Figure 4. Memory requirement comparison of Random Interleaver and Tree Based Interleaver.
Figure 4 demonstrates the memory requirement of RI and TBI. The memory requirement of RI is dependent on
user count [3] [4] while that of TBI is constant [15] due to use of only two master interleaving sequences for
generating the other user specific interleaving sequences. The memory required by Tree Based Interleaver
generation method is extremely less than that required for random interleaver generation method [3] and is
independent of user count.
In this section, we present simulation results to demonstrate the performance of the MRC diversity scheme with
IDMA systems. Here we refer the channel as slow fading Rayleigh channel. The interleavers used in simulations
are random interleaver [3] and tree based interleaver [15]. The block length is 200 and frame length is 65536
bits/frame with spread length to be 16. The iterations selected for simulation in receiver is 15. The simulations
have been performed for one transmitter and two receiver arrangement in the case of receiver diversity. On the
other hand, in the case of transmit diversity two transmitter antennas and one receiver antenna is used for
analysis. It is also assumed that transmit power from two antenna in transmit diversity is same as the power
transmit by single antenna in receiver diversity.
Figure 5 demonstrates the performance of IDMA scheme with using random interleaver. Here in receiver as well
as in transmit diversity two branches maximal ratio combining scheme is used for implementation of space
diversity technique. In this case, the degree of complexity remains similar to that in simple IDMA systems. The
BER performance with maximal ratio combining diversity is better than without using any diversity technique in
fading environment.
Figure 5. Performance of RI-IDMA with transmit and receive diversity
Figure 6 shows the BER performance of IDMA scheme using tree based interleaver with both diversity schemes.
From this figure we can see that the performance of IDMA system with MRC diversity is far better than that
without diversity also the performance of Tree based interleaver comes out to better in the case of transmit
diversity.
0 10 20 30 40 50 60 70 80 90 100
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
x 10
6
User Number
MemoryRequirementofInterleaver
With Random Interleaver
With Tree Based Interleaver
2 4 6 8 10 12 14 16 18
10
-6
10
-5
10
-4
10
-3
10
-2
10
-1
Eb/No
BitErrorRate
IDMA without diversity
IDMA with receiver diversity
IDMA with transmit diversity
k65536
k=65536

31
Figure 6. Performance of TBI-IDMA IDMA with transmit and receive diversity
6. CONCLUSIONS
We have employed diversity scheme for reducing the fading problem in IDMA systems. The results have taken
for transmit as well as receive diversity configuration. Simulation results show that IDMA scheme performs
better with both type of diversity schemes. Although it is not the intention to compare transmitter diversity to
receiver diversity, because it is already stated that both the diversity schemes performs nearly [2], but having
distinguish application area.
It is already explained that tree based interleaver performs good, near to random interleaver [13],but in the
reference of complexity and memory requirement it takes edge on random interleaver [figure 4]. So, both the
interleavers are taken for study and simulations show good BER performance.
IDMA with suitable diversity technique can generate fruitful results in the area of wireless communication. Since
IDMA inherits all the merits of DS-CDMA in addition to its own advantages, existing CDMA systems may be
enhanced by IDMA systems and study can also enhanced to Multiple input and multiple output (MIMO) antenna
system to improve the diversity order and hence the performance of IDMA communication system.
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0 2 4 6 8 10 12 14 16 18
10
-6
10
-5
10
-4
10
-3
10
-2
10
-1
Eb/No
BitErrorRate
IDMA without diversity
IDMA with recieve diversity using TBI
IDMA with transmit diversity using TBI
k=65536
k=65536

32
M. Shukla, V.K. Srivastava, S. Tiwari, “Analysis and Design of Optimum Interleaver for Iterative Receivers in
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