Optimization of Resource Allocation for Heterogeneous Services in OFDM Based Cognitive Radio Networks Using Artificial Bee Colony

In adaptive resource allocation problems regarding multiuser Orthogonal Frequency Division Multiplexing (OFDM) systems, a lot of focus has been on homogenous traffic that solely consists of either guaranteed services or best effort services. In this paper, we inspect a multiuser OFDM system with heterogeneous traffic. Our goal is to simultaneously, maximize the capacity of all the Secondary Users (SUs) with non-real traffic and to fulfill the minimum data rate requirement of real time SUs, while keeping the interference to the Primary User (PU) less than the predefined threshold value. In order to solve this non-convex problem, we have employed Artificial Bee Colony algorithm. The simulation results are evidencing that the proposed methodology generates the optimum results and is quite applicable for practical scenarios.