Joint Optimization of Spectrum Sensing and Transmit Power in Energy Harvesting-Based Cognitive Radio Networks

Proliferation of mass market applications and all forms of smart devices have driven the explosive growth of wireless sensor data traffic in recent years. In spite of notable advancements in wireless sensor technologies, energy scarcity due to a limited battery capacity still remains a critical impediment to consumer electronics applications. Thus, the energy harvesting (EH) technology, utilizing extra energy collected from radio frequency (RF) signals, is regarded as a promising solution for addressing the battery problem. This paper presents, analyzes, and discusses a joint sensing and power allocation scheme for cognitive radio in conjunction with EH, in which a secondary transmitter can harvest energy from RF signals transmitted by a primary transmitter during spectrum sensing. We formulate a non-convex optimization problem to find the optimal sensing time and power allocation for maximizing energy efficiency, while satisfying the constraints on the amount of harvested energy and interference at primary receivers. Using nonlinear fractional programming, the original problem can be reformulated into a tractable convex one, and an energy efficient resource allocation algorithm is devised while taking into account RF EH. Simulation results are used to verify the optimality of the proposed scheme, where the secondary network can accomplish maximum energy efficiency.