文献类型：会议论文

英文题名：Robust Secure Beamforming for Multi-Receiver Multi-Eavesdropper MIMO SWIPT Systems

作者：Yu, Yao[1,2,3];Liu, Shumei[1,2];Yuan, Weina[4];Yeoh, Phee Lep[3];Vucetic, Branka[3];Li, Yonghui[3]

机构：[1]Northeastern Univ, Sch Comp Sci & Engn, Shenyang 110819, Peoples R China;[2]Northeastern Univ, Key Lab Intelligent Comp Med Image, Minist Educ, Shenyang 110819, Peoples R China;[3]Univ Sydney, Sch Elect & Informat Engn, Sydney, NSW, Australia;[4]East China Univ Sci & Technol, Sch Informat Sci & Engn, Shanghai 200237, Peoples R China

会议论文集：IEEE Global Communications Conference (GLOBECOM) on Advanced Technology for 5G Plus

会议日期：DEC 07-11, 2020

会议地点：ELECTR NETWORK

语种：英文

外文关键词：Simultaneous wireless information and power transfer (SWIPT); physical layer security; multiple-input-multiple-output (MIMO); artificial noise (AN)

摘要：In this paper, we consider a multiuser multiple-input multiple-output (MIMO) downlink communication system with simultaneous wireless information and power transfer (SWIPT). In particular, we focus on a realistic and efficient multi-receiver multi-eavesdropper MIMO SWIPT system, in which the channel state information (CSI) of each legitimate receiver and energy receiver (i.e., potential eavesdropper) is partially known to the transmitter. Based on this, we propose a robust artificial noise (AN)-aided secure transmission scheme for the system, where the channel uncertainties are modeled by the worst-case model. In the proposed scheme, we aim to maximize the worst-case achievable secrecy rate under the transmit power constraint and the energy harvesting (EH) constraint, by jointly optimizing the transmit precoding matrix and the AN covariance matrix. We utilize the S-Procedure and Taylor series approximation to transform the non-convex problem. Then, we apply the interior point method to tackle the transformed convex problem, obtaining the approximate optimal matrices and the corresponding maximum worst-case secrecy rate. Simulation results show that our proposed scheme achieves significant performance improvements in terms of convergence and the worst-case achievable secrecy rate.