Energy-Efficient Cooperative Spectrum Sensing With Reporting Errors in Hybrid Spectrum Sharing CRNs

Recently, cooperative spectrum sensing (CSS) in cognitive radio networks has been extensively researched. However, most of the studies mainly focus on maximizing the spectral efficiency while the energy consumption is generally ignored. However, since the secondary users (SUs) are usually battery-powered devices, energy saving is very important. This paper studies the mean energy efficiency (EE) maximization problem of the CSS system using the hybrid spectrum sharing (HSS) scheme. Specifically, the effects of imperfect spectrum sensing and reporting channel errors on the EE are considered. Our goal is to maximize the mean EE of SUs while maintaining the detection accuracy by jointly optimizing the sensing time and the number of cooperative SUs, subject to the SUs' average/peak transmission power constraints (ATPC/PTPC) and minimum data rate constraint, and the average interference power constraint of primary user. To address the non-convexity of the optimization problem, an energy-efficient iterative power allocation algorithm is developed. Simulations compare the achievable mean EE under ATPC/PTPC with three hard combining fusing rules using the HSS scheme and the opportunistic spectrum access (OSA) scheme, respectively; the results show that our proposed HSS scheme can obtain higher mean EE than the conventional OSA scheme and that the EE achieved under ATPC is better than that under PTPC. Moreover, among the three hard combining fusing rules, the Majority rule has the best EE.