Energy-Efficient Cooperative Spectrum Sensing for Hybrid Spectrum Sharing Cognitive Radio Networks

Recently, many technological issues concerning cooperative spectrum sensing (CSS) of cognitive radio networks (CRNs) have been studied, but most of them focus on maximizing spectral efficiency (SE) under the opportunistic spectrum access (OSA) scheme. In this paper, we investigate the mean energy efficiency (EE) maximization problem under the hybrid spectrum sharing (HSS) scheme. Due to channel fading, the effects of reporting channel errors on the EE should he considered. Specifically, the minimum transmit data rate constraint is imposed to ensure the quality of service (QoS) requirements of secondary users (SUs). Our goal is to maximize the mean EE while maintaining the sensing accuracy by jointly optimizing the sensing slot length and the number of cooperative SUs, subject to the rate constraint and the transmit and interference power constraints. To address the non-convexity of the optimization problem, we propose an energy-efficient CSS iterative power adaptation algorithm. Simulation results demonstrate that the proposed algorithm can achieve higher average EE than the conventional OSA scheme.