Robust Beamforming Design for SWIPT-Enabled Hierarchical Cognitive Radio Networks

Abstract

In this paper, we investigate the robust beamforming design for simultaneous wireless information and power transfer (SWIPT)-enabled hierarchical cognitive radio (HCR) where the primary receiver (PR) is allowed to harvest energy when the secondary system (SS) radiates its information to the secondary receiver (SR). The design objective is to maximize the transmission rate of SS provided that the harvested energy and outage probability of the primary system (PS) are guaranteed. The optimization problem, however, is not convex due to the probability-based constraints introduced by the imperfect channel state information (CSI). To obtain the tractable solution, we apply the Bernstein-type inequality and sphere bounding so that the problem can be approximated by convex formulations. Then, the resultant problems can be efficiently solved with CVX tools. Simulation results demonstrate that the designs can effectively improve the system performance under imperfect CSI environments.