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Throughput Optimization in Cooperative Communications using Evolutionary Algorithms

Abhishek Singh, Ashish Raman, Deepti kakkar

This paper illustrates the results of the throughput of Secondary User (SU) in cognitive radios under cooperative scenario with the use of evolutionary algorithms in the presence of additive white Gaussian (AWGN) noise. In this work, the performance of half-voting and OR fusion rule is studied in terms of Pd Vs Pf curves. OR fusion rule is found to be most suitable in cooperative scenario. Then, Particle Swarm Optimization (PSO) and Biogeography Based Optimization (BBO) algorithms are implemented using OR fusion rule to enhance the throughput of cognitive users by taking in to account the protection of primary (licensed) users. The probability of detection is set to 0.9 for protection purpose. Simulations results in terms of co-operations shows that PSO performs better initially but as numbers of co-operations increases PSO performance degrades.