GGRA: A Feasible Resource Allocation Scheme by Optimization Technique for IEEE 802.16 Uplink Systems

Generally, optimization techniques for resource allocation of OFDMA systems are infeasible for real-time applications. In this paper, we propose a genetic algorithm with subscriber station (SS) grouping resource allocation (GGRA) scheme for IEEE 802.16 uplink systems. The GGRA scheme firstly designs a rate assignment strategy, applied with a predefined residual lifetime, to allocate resource to each service dynamically. It then aggregates high correlation SSs into the same group, where the SSs will be allocated to different slots so as to avoid mutual user interference. Finally, the GGRA scheme finds an optimal assignment matrix for the system by the genetic algorithm, based on the SS groups to greatly lessen the computation complexity. The GGRA scheme can also maximize system throughput and fulfill QoS requirements. Simulation results show that the proposed GGRA scheme performs better than the EFS algorithm [] and the MLWDF algorithm [] in system throughput, voice/video packet drop rate, unsatisfied ratio of HTTP users/packets, and FTP throughput. The computation complexity of the GGRA scheme is also tractable and thus feasible for real-time applications.