Joint Optimal Design of Sensing Time and Transmission Power for Maximizing Energy Efficiency in Cognitive Radio System

The average throughput of a cognitive radio (CR) system can be increased by performing spectrum handoff, however, it may cause high energy consumption. Therefore, it is necessary to build an energy efficient CR system while performing spectrum handoff. In this paper, a joint optimization problem of sensing time and transmission power is formulated to maximize energy efficiency (EE) of a CR system subject to the constraint on sufficient protection to the primary users while considering spectrum handoff. Swarm intelligence techniques, namely particle swarm optimization (PSO), human behavior-based PSO (HPSO), and whale optimization algorithm (WOA) are used in this study to evaluate joint optimal sensing time and transmission power. The performance comparison of the three techniques is presented in terms of fitness function (EE) and average computational time. The simulation results show that the three techniques achieve a unique joint optimal sensing time and transmission power at which EE attains the highest peak; WOA outperforms PSO and HPSO in terms of average computational time. The impact of joint optimization of sensing time and transmission power, the impact of variation of target detection probability as well as the variation of number of channels on EE are discussed. A quantitative comparison is also performed between the proposed work and the existing work.