User Selection with Energy Efficiency for Cooperative Spectrum Sensing in Energy Harvesting Cognitive Radio Networks

In this paper, we consider a RF energy harvesting cognitive radio network (CRN) in which cooperating secondary users (SUs) are equipped with energy harvesting capabilities. The SUs can harvest energy by converting the received radio frequency (RF) signal into electricity. It is assumed that the SUs have different SNRs due to their distances from the primary user (PU). Our objective is to maximize the energy efficiency of the CRN subject to the sensing accuracy constraint and energy constraint by finding the optimal SUs to participate in the cooperative spectrum sensing. The problem is solved analytically based on the convex optimization framework. After acquiring the optimal conditions based on karush-Kuhn-Tucker (KKT)conditions, an iterative algorithm is proposed to find the SUs for spectrum sensing. Since the problem is a NP-complete problem, we simplify it through mapping discrete parameter into real domain. Therefore, we can decide which SUs are selected for spectrum sensing at a lower computational complexity. A priority-based SU selection algorithm in cooperative spectrum sensing is proposed to improve the energy efficiency. Simulation results show that the proposed approach can improve the energy efficiency.