Electrical and Computer Engineering Department-College of Engineering-Sultan Qaboos University
Multi-user Detection Genetic Algorithm in Code Division Multiple
Access (CDMA) Communication System
Mubarak Mohammed AL Sawafi
Abstract
The capacity of "pseudo-orthogonal" code division multiple access (PO-CDMA) can be impaired
by two problems; near-far effect and multiple access interference (MAl). The use of conventional
matched filter detector for multiple users in CDMA fails to combat any of these problems. On
the other hand, the use of maximum likelihood sequence estimation detector provides excellent
results but involves high computational complexity, which is exponential in the number of
actives users. The objective of this work is to develop sub-optimal detectors that have reasonable
computational complexity and their performance is comparable to that of the optimum receivers.
Two different approaches of GA are proposed to meet this target. Attention is focused on the
downlink (base-to-mobile) of a direct sequence type of CDMA (DS-CDMA) cellular system. In
other words, the synchronous case is only considered in this project. The conventional DSCDMA system is analyzed theoretically and through simulation to provide a reference
performance level. The influence that MAl might have in the performance is also discussed. The
maximum likelihood sequence estimation detector is then investigated. This detector is called
sometimes in the literature as the optimal detector. Its performance inmulti-user DS-CDMA
system is presented via simulation results. This provides a reference of the best performance
level that might be achieved in multi-user environment in CDMA systems. Hence, the achieved
probability of error is compared with that one attained with both the conventional and optimal
detectors. Methods of using genetic algorithms in multi-user detection in CDMA systems are
considered. Two types of genetic algorithms are used: simple genetic algorithm (SGA) and micro
genetic algorithm .)AGlI(The BER, in addition to the decoding time, are used as measures to
assess the performance of both genetic detectors compared to_ that of the optimal detector. A
simulation of SGA detector using the outputs of - conventional detector as an initial stage is
presented. Moreover, the effect of some genetic parameters in the system's performance is
studied. The SGA detector is found capable of achieving results close to the optimal detector but
after a large number of iterations. As a result, decoding time becomes long compared to the
optimal. Hence, the SGA is considered not to be a suitable suboptimal detector. The concept of
Electrical and Computer Engineering Department-College of Engineering-Sultan Qaboos University
micro genetic algorithm is then introduced. A comparison of the differences between the two
techniques of the genetic algorithm adopted in this work is made. Additionally, the performance
of micro genetic algorithm detector is presented using the simulation results. The influence of
increasing the number of generation in term of performance and decoding time is discussed. The
outputs of conventional and decorrelator are tried separately as initial stages. The AGlIdetector
gives close results to the optimal and in a shorter time than the case in the optimal detector.
Therefore, it can be regarded as a suboptimal detector. Furthermore, it is found that the
decorrelator detector is a better choice, as an initial stage, compared to the conventional detector.
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