Energy-efficient sensor selection for multi-channel cooperative spectrum sensing based on game theory

This paper considers a wireless cognitive sensor network (WCSN) composed of distributed sensors that cooperatively sense multiple channels. Since the energy consumption of WCSNs is an important issue besides sensing quality requirements, the paper proposes a sensor selection method for multi-channel cooperative spectrum sensing that reduces energy consumption under detection quality constraints, for scenarios that the recharge of sensors is difficult or impossible. It is assumed that the sensors cannot sense more than one channel in a sensing duration because of hardware limitations. This problem is modeled as a coalition game in which sensors act as game players and decide to make disjoint coalitions. Each coalition senses one of the channels while guaranteeing that the necessary detection and false alarm probability thresholds are satisfied. Other nodes, that decide to sense none of the channels, turn off their sensing module at the sensing period, to extend the network lifetime. A novel proper utility function is proposed based on the energy consumption, false alarm probability, and detection probability of sensors. This paper proposes an efficient algorithm to reach a Nash-stable coalition structure. The proposed algorithm is compared with the optimal algorithm and two other existing algorithms through simulations. In addition, the computational complexity of the proposed algorithm is analyzed.