Genetic Algorithm based Adaptive Resource Allocation in OFDMA System for Heterogeneous Traffic

摘要

An adaptive resource allocation scheme for QoS oriented OFDMA system, which schedules two different utility functions for the Real-time/Non Real-time traffic simultaneously, is proposed in this paper. Instead of partial consideration of uniform kinds of QoS, we introduce an updating ratio factor to schedule users of heterogeneous traffic. Due to the complex optimization objective, the general convex optimal methods are no longer feasible. We are motivated to study a heuristic natural genetic approach to solve this problem. Due to the weak convergence of Genetic Algorithm (GA), we improve it by a well-selected initial population. Numerical results are presented to illustrate that our scheme not only tackles the diverse QoS requirement but also alleviates the unfairness between real-time and non-real-time services under various traffic loads.