Optimal spectrum sensing in energy harvesting cognitive radio systems

In this paper, we consider a cognitive radio system with energy harvesting, in which the secondary user operates in a saving-sensing-transmitting (SST) fashion. We investigate the tradeoff between energy harvesting, channel sensing and data transmission and focus on the optimal SST structure to maximize the SU's expected achievable throughput. We consider imperfect knowledge of energy harvesting rate, which cannot be exactly known and only its statistical information is available. By formulating the problem of expected achievable throughput optimization as a mixed-integer non-linear programming one, we derive the optimal save-ratio and number of sensed channels with in-depth analysis. Simulation results show that the optimal SST structure outperforms random one and performance gain can be enhanced by increasing the SU's energy harvesting rate.