Downlink Resource Allocation in OFDMA using HPSOGA AND HGAPSO

Abstract

Resource allocation is very essential at the base station (BS) to have a fair allocation of resources among the users. Orthogonal Frequency Division Multiple Access (OFDMA) allows many users to transmit simultaneously on different subchannels per Orthogonal Frequency Division Multiplexing (OFDM) symbol. The system capacity of downlink OFDMA system can be maximized by adaptively assigning subchannels to the user with the best possible gain using hybrid particle swarm optimization and genetic algorithm (HPSOGA). PSO and GA are combined in a sequential manner resulting in two different techniques namely HPSOGA and HGAPSO. The idea behind the hybrid algorithm is to use PSO to generate initial population of GA and vice-versa. Simulation results show that HPSOGA and HGAPSO provide capacity improvement over PSO. Among the two hybrid models, compared to the PSO method HGAPSO provides improvement in fairness with respect the users.