Energy-efficient design of channel sensing in cognitive radio networks

In cognitive radio (CR) networks, cooperation can greatly improve the spectrum sensing performance. However, more energies are required in the local spectrum sensing and sensing results reporting process. When the energies of the secondary users (SUs) are constrained, using their energies efficiently is a crucial problem, which must be considered. In this paper, the energy efficiency is defined as the ratio of the average channel throughput and the average energy consumption. We focus on the optimization of the final decision threshold to maximize the energy efficiency for additive white Gaussian noise (AWGN) channels, Nakagami fading channels and Rayleigh fading channels. An energy efficient optimization strategy (EEOS) is proposed to calculate the optimal solutions. Computer simulations show that fundamental improvement of the energy efficiency can be obtained by using our proposed EEOS, and there is an optimal number of cooperating SUs that can maximize the energy efficiency.