Throughput Maximization of the Cognitive Radio Using Hybrid (Overlay-Underlay) Approach with Energy Harvesting

Energy management is an acute challenge for battery powered devices. In this work, we consider a cognitive radio (CR) equipped with energy harvested finite capacity battery. The cognitive radio harvests energy from radio frequency (RF) source (primary channel) as well as from non-RF sources (ambient sources such as wind, solar, and vibration). Energy harvesting from the primary channel occurs only if the channel is found in busy state and energy of the signal is above a certain threshold. The harvested energy is consumed in channel sensing, processing and subsequent transmission. The spectrum sensing decision is controlled optimally by partially observable Markov decision process (POMDP) according to the available energy of the CR and status of the primary channel. Such decision results in an optimized utilization of energy. The cognitive radio enhances throughput by transmitting in the hybrid mode adapting the overlay or underlay mode depending on the sensing and transmission energy. Throughput improvement of the cognitive radio is shown through simulations where throughput in the hybrid mode is compared with the overlay-only mode. Simulations also show the effect of channel idle probability and harvested energy on the throughput.