Energy-Efficient Optimal Sensing and Resource Allocation of Soft Cooperative Spectrum Sensing in CRNs

Cooperative spectrum sensing (CSS) is an effective method to combat channel fading and improve sensing accuracy. However, cooperation also increases energy consumption, which in turn decreases the network performance. In this paper, we investigate the energy-efficient optimal sensing and resource allocation of soft combing CSS in cognitive radio networks. We aim at maximizing the average energy efficiency (EE) of secondary users while guaranteeing the detection performance and the quality of service of primary user by jointly optimizing the energy detector threshold, number of participating users, sensing time and transmit power. To address the non-convexity of the formulated problem, the expression of optimal energy detector threshold is derived first. Then, a sub-optimal alternating iterative algorithm is proposed to solve the problem efficiently. Simulations demonstrate the superiority and optimality of the proposed algorithm. The results show that our proposed algorithm significantly improve the EE compared with existing schemes.