Particle Swarm Optimization Based Resource Allocation in Orthogonal Frequency-division Multiplexing

Current cellular wireless data communications require wide availability and satisfying quality of service to keep up with the rising number of wireless devices. It is challenging for the service provider to cater to different kinds of upcoming new services and applications as data rates vary apart in that respect. For that reason, it is of paramount importance to adaptively utilize the radio resources which are limited and valuable. The ability of Orthogonal Frequency-division Multiplexing Access (OFDMA) to split the entire bandwidth into smaller sub-carriers allows adaptive resource allocation to be performed in downlink communications. However, due to the time-varying nature of the wireless channel, not all links experience the same channel response. Therefore, this situation is akin to a strategic combination problem to find the best allocation out of the huge combinations according the current channel characteristics. This paper presents an evolutionary method, particle swarm optimization (PSO), to optimally allocate the rates and sub carriers to multiple users. The results display good convergences towards the optimal solution for a minimal transmit power allocation. At transmission intervals, the cellular base station will be able to use the best allocation relating to channel conditions of any point in time.