A novel frame structure for centralized cooperative cognitive networks to achieve overhead-throughput tradeoff

This paper addresses overhead-throughput tradeoff issues for the centralized cooperative cognitive network. Taking the reporting overhead into consideration, a novel frame structure consisting of M + 1 subframes is proposed to maximize the achievable throughput of the cognitive network. According to the channel condition between primary user (PU) and each secondary user (SU), the overhead-throughput tradeoff problem is investigated in two scenarios. For scenario I, we focus on optimizing the number of reporting secondary users (SUs) to achieve overhead-throughput tradeoff. For scenario II, we not only optimize the number of reporting SUs, but also design reporting SUs´ selection methods. Numerical results show that under the proposed frame structure, there exists an optimal number of reporting SUs to achieve overhead-throughput tradeoff, and maximize the achievable throughput of the cognitive network.