arXiv · 1808.07689
Optimal Precoder Designs for Sum-utility Maximization in SWIPT-enabled Multi-user MIMO Cognitive Radio Networks
Abstract
In this paper, we propose a generalized framework that combines the cognitive radio (CR) techniques for spectrum sharing and the simultaneous wireless information and power transfer (SWIPT) for energy harvesting (EH) in the conventional multi-user MIMO (MuMIMO) channels, which leads to an MuMIMO-CR-SWIPT network. In this system, we have one secondary base-station (S-BS) that supports multiple secondary information decoding (S-ID) and secondary EH (S-EH) users simultaneously under the condition that interference power that affects the primary ID (P-ID) receivers should stay below a certain threshold. The goal of the paper is to develop a generalized precoder design that maximizes the sum-utility cost function under the transmit power constraint at the S-BS, and the EH constraint at each S-EH user, and the interference power constraint at each P-ID user. Therefore, the previous studies for the CR and SWIPT systems are casted as particular solutions of the proposed framework. The problem is inherently non-convex and even the weighted minimum mean squared error (WMMSE) transformation does not resolve the non-convexity of the original problem. To tackle the problem, we find a solution from the dual optimization via sub-gradient ellipsoid method based on the observation that the WMMSE transformation raises zero-duality gap between the primal and the dual problems. We also propose a simplified algorithm for the case of a single S-ID user, which is shown to achieve the global optimum. Finally, we demonstrate the optimality and efficiency of the proposed algorithms through numerical simulation results.
Explore related subjects
Keep this discovery
Changick Song, Hoon Lee, Kyoung-Jae Lee. 2018-08-23. Optimal Precoder Designs for Sum-utility Maximization in SWIPT-enabled Multi-user MIMO Cognitive Radio Networks. https://doi.org/10.1109/jsyst.2018.2875762
Cite the original work for its findings. Save a collection to share your selection of sources.