Evolutionary Search for Energy-Efficient Distributed Cooperative Spectrum Sensing

This paper concerns the energy efficiencyoptimization for distributed cooperative spectrum sensing. In the considered distributed spectrum sensing system, each sensor measures the local test statistic for the target spectrum bands and these measurements will be combined together through a weighted consensus protocol. In this way, all the sensors are able to make contributions to the improvement of the spectrum sensing performance. However, the significance of a sensor’s contribution depends on its local signal to noise ratio. From energy efficiency perspective, it is not reasonable to invest energy on the sensors that bring little benefits. In this paper, we formulate an energy efficiency optimization framework for distributed spectrum sensing. Our objective is to achieve the target spectrum sensing performance with as few sensors as possible. Accordingly, a genetic algorithm based approach and a particle swarm optimization based approach are proposed for this problem.