Simulation of QoS parameters in cognitive radio system using SMO algorithm

Abstract

Cognitive radio (CR) is the current growing technology in wireless communication field and has increase the ability to use the frequency spectrum more properly. The main objective of cognitive radios is to sense the surrounding and use primary user's vacant spaces and allot them to the secondary users without interference each other. This paper presents the optimal solution and optimizes the Quality of services (QoS) parameters to minimum i.e. smaller as compare other solutions which are induced by different optimization techniques Simulated Annealing (SA) and Genetic algorithm (GA). The proposed algorithm called spider monkey optimization algorithm (SMO). SMO is a swarm intelligence technique which works on foraging behaviour of spider monkeys. SMO is tentative and lapse based synergetic iterative process. Spider monkeys have been categorized as fusion-fission social structure (FHSS) based animals and they divides into smaller subgroups and search food. The proposed algorithm has been used to optimize the performance of QoS parameters in terms of minimum power consumption, minimum bit error rate (BER), maximum throughput, minimum interference and maximum spectral efficiency. The simulation results shows that the fitness scores obtained by the proposed algorithm i.e. SMO are better (smaller) than SA and GA algorithm in the optimization of QoS parameters of cognitive radio system. The proposed algorithm is better (smaller) than the existing algorithm.