Energy-Efficiency Maximization for Cooperative Spectrum Sensing in Cognitive Sensor Networks

Abstract

Spectrum sensing is the prerequisite of opportunistic spectrum access in cognitive sensor networks (CSNs) as its reliability determines the success of transmission. However, spectrum sensing is an energy-consuming operation that needs to be minimized for CSNs due to resource limitations. This paper considers the case where the cognitive sensors cooperatively sense a licensed channel by using the CoMAC-based cooperative spectrum sensing (CSS) scheme to determine the presence of primary users. Energy efficiency (EE), defined as the ratio of the average throughput to the average energy consumption, is a very important performance metric for CSNs. We formulate an EE-maximization problem for CSS in CSNs subject to the constraint on the detection performance. In order to address the non-convex and non-separable nature of the formulated problem, we first find the optimal expression for the detection threshold and then propose an iterative solution algorithm to obtain an efficient pair of sensing time and the length of the modulated symbol sequence. Simulations demonstrate the convergence and optimality of the proposed algorithm. It is also observed in simulations that the combination of the CoMAC-based CSS scheme and the proposed algorithm yields much higher EE than conventional CSS schemes while guaranteeing the same detection performance.