Optimization of Multiuser Multichannel Cognitive Radio Networks with Wireless Information and Power Transfer

This paper considers a multiuser multichannel simultaneous wireless information and power transfer (SWIPT) cognitive radio (CR) network, where a set of secondary users (SUs) simultaneously harvests energy and decodes information using the same signals transmitted from a cognitive base station (CBS). Power splitting is adopted to realize SWIPT by splitting the signal power into two portions, where one portion is used for energy harvesting and the other portion is used for information decoding. We investigate the problem of maximizing the sum rate of the SUs by optimizing the channel allocation, the power allocation and the power splitting ratios. We propose an efficient iterative algorithm based on alternating direction optimization method (ADOM) to iteratively optimize the channel allocation, the power allocation and the power splitting ratios until convergence. We show that the proposed algorithm converges fast and outperforms other reference algorithms.