Fast Optimal Resource Allocation is Possible for Multiuser OFDM-Based Cognitive Radio Networks with Heterogeneous Services

Abstract

In this paper we study the resource allocation in multiuser orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) networks, where secondary users (SUs) have flexible traffic demands, including heterogeneous real-time (RT) and non-real-time (NRT) services. We try to maximize the sum capacity of the NRT users and maintain the minimal rate requirements of the RT users simultaneously. Additionally, the interference introduced to primary users, which is generated by the access of the SUs, should be kept below a predefined threshold, which makes the optimization task more complex. The contribution of this work is two folds. First, we show that the formulated optimization problem has a special structure which can be exploited to implement a fast barrier method to obtain the optimal solution with a reasonable complexity. Second, we propose an effective measurement criterion to normalize OFDM subchannels' achievable rates, based on which we develop simple but efficient heuristic algorithm for subchannel assignment and power distribution. Simulation results show that our proposed resource allocation schemes work quite well for concerned wireless scenarios. The fast barrier method converges very fast and can always work out the optimal solution, while the heuristic algorithm produces solution close to the optimal with much lower complexity.