Joint Optimization Framework for IRS-assisted Multicarrier MIMO SWIPT

• Published in: 2022 IEEE/CIC International Conference on Communications in China (ICCC) pp. 627 - 631
• Main Authors: Peng, Xingxiang, Wu, Peiran, Tan, Hongzhou, Xia, Minghua
• Format: Conference Proceeding
• Language: English
• Published: IEEE 11.08.2022
• Subjects: Benchmark testing; Intelligent reflecting surface; Matrix decomposition; MIMO; multicarrier; power splitting; Precoding; Programming; Simulation; Simultaneous wireless information and power transfer; Wireless communication
• DOI: 10.1109/ICCC55456.2022.9880739

This paper studies an intelligent reflecting surface (IRS)-assisted multicarrier multiple-input and multiple-output (MIMO) power splitting (PS)-based simultaneous wireless information and power transfer (SWIPT) system. In particular, we aim to minimize the sum MSE by jointly designing the transmit precoding matrices, the equalization matrices, the IRS matrix, and the PS ratio, under the transmit power and harvested power constraints. Since the formulated problem is highly non-convex, we develop an alternating optimization (AO)-based algorithm to find a high-quality sub-optimal solution. Specifically, the optimal equalization matrices are first derived in closed-form. Afterward, the semi-definite programming (SDP) technique is employed to jointly optimize the precoding matrices and the PS ratio. Finally, the optimization of the reflection-coefficients matrix is decomposed into a series of independent sub-problems, and the convex relaxation technique is adopted to handle these subproblems. Simulation results verify that the AO-based algorithm can significantly decrease the sum MSE of the system compared to conventional benchmarks.