Energy-efficient node selection and power control in cooperative spectrum sensing

In cooperative spectrum sensing, wireless reporting channels (from local sensing nodes to fusion center) may suffer severe unreliability, which would make a correct local sensing result incorrect while received by fusion center. In this study, the reliability of the sensing result transmission from local sensor to fusion center is considered, and to make spectrum sensing more energy efficient, appropriate nodes were selected and activated to participate in spectrum sensing while others remain idle. To further reduce energy consumption, transmission power control for sensing nodes was optimized. Total energy consumption minimization was modeled as a mixed discrete and continuous variable optimization problem and the binary particle swarm optimization with power control (BPSO-PC) was proposed. BPSO-PC adjusted the sensing node transmission power and properly selects nodes for cooperative spectrum sensing. Simulation results showed that total energy consumption was significantly reduced compared with BPSO and three other sensing nodes selection algorithms.