Reducing Computational Complexity in DS-CDMA using Swarm Optimization Techniques
July 13, 2012
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Akram Rashid, Assistant Professor, Zahooruddin, Assistant Professor, Dr. Ijaz Mansoor Qureshi, Dr. Aamer Saleem Chaudhry, Professor
In commercial CDMA systems the signal strength is extensively effected by the Multiple Access Interference(MAI). Many techniques have been employed to reduce the effect of MAI. In the beginning Matched Filters are being used to handle MAI problems. In Multiuser detectors following two filters, code matched filter and multiuser linear filter are used to handle the MAI problem. But because of asynchronous operation of these filters the computational complexity of the system is increased. And hence the efficiency of the system drastically effected. This Multiuser technique is based on sub-symbol and in the sub-symbol scheme, data symbols of the users are partitioned Matched filter techniques have been successfully utilized in IS -95 standard). But with in to sub-symbols such that the resulting sub-symbols from different users are time aligned at the receiver side.
The optimal linear filters operate in each sub-symbol interval, and the filtered outputs are processed using various evolutionary Algorithms. With the matched filter technique the number of users become limited in DS -CDMA. When the number of users are increased in DS -CDMA, the bit error rate(BER) for individual user is also increased. Researchers have used many techniques to eradicate this problem. In this research paper two swarm optimization techniques( PSO & GA) have been used to handle the problem of computational complexity problem. The comparison is made in between these two techniques. It is analyzed that PSO has a edge over GA in reducing computational complexity.
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