Bee colony optimization aided adaptive resource allocation in OFDMA systems with proportional rate constraints
Orthogonal frequency division multiple access (OFDMA) is a promising technique, which can provide high downlink capacity for the emerging wireless systems. The total capacity of OFDMA can be maximized by adaptively assigning subcarriers to the users with the best gains for those subcarriers, with power subsequently distributed by water-filling. In this paper, we propose the use of artificial bee colony (ABC) algorithm combined with Debs selection mechanism to handle the constraints. In this scheme, a probabilistic selection scheme assigns probability values to feasible solutions based on their fitness values and to infeasible individuals based on their violations, to allocate the resources to the users in downlink OFDMA system. Specifically we propose two approaches for resource allocation in downlink OFDMA systems using ABC algorithm. In the first approach, ABC algorithm is used for subcarrier allocation only, while in second approach the ABC algorithm is used for joint subcarrier and power allocation. It is shown that both these approaches obtain higher sum capacities as compared to that obtained by previous works, with comparable computational complexity. It is also shown that the joint subcarrier and power allocation approach provides near optimal results at the cost of slightly higher computational cost.
bee colony optimization resource allocation orthogonal frequency division multiple access sum capacity computational complexity