TY - GEN
T1 - AN-aided secure transmission in multi-user MIMO SWIPT systems
AU - Zhu, Zhengyu
AU - Wang, Ning
AU - Chu, Zheng
AU - Wang, Zhongyong
AU - Lee, Inkyu
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/6/8
Y1 - 2018/6/8
N2 - In this paper, an energy harvesting scheme for a multi-user multiple-input-multiple-output (MIMO) secrecy channel with artificial noise (AN) transmission is investigated. Joint optimization of the transmit beamforming matrix, the AN covariance matrix, and the power splitting ratio is conducted to minimize the transmit power under the target secrecy rate, the total transmit power, and the harvested energy constraints. The original problem is shown to be non-convex, which is tackled by a two-layer decomposition approach. The inner layer problem is solved through semi-definite relaxation, and the outer problem is shown to be a single-variable optimization that can be solved by one-dimensional (1-D) line search. To reduce computational complexity, a sequential parametric convex approximation (SPCA) method is proposed to find a near-optimal solution. Furthermore, tightness of the relaxation for the 1-D search method is validated by showing that the optimal solution of the relaxed problem is rank-one. Simulation results demonstrate that the proposed SPCA method achieves the same performance as the scheme based on 1-D search method but with much lower complexity.
AB - In this paper, an energy harvesting scheme for a multi-user multiple-input-multiple-output (MIMO) secrecy channel with artificial noise (AN) transmission is investigated. Joint optimization of the transmit beamforming matrix, the AN covariance matrix, and the power splitting ratio is conducted to minimize the transmit power under the target secrecy rate, the total transmit power, and the harvested energy constraints. The original problem is shown to be non-convex, which is tackled by a two-layer decomposition approach. The inner layer problem is solved through semi-definite relaxation, and the outer problem is shown to be a single-variable optimization that can be solved by one-dimensional (1-D) line search. To reduce computational complexity, a sequential parametric convex approximation (SPCA) method is proposed to find a near-optimal solution. Furthermore, tightness of the relaxation for the 1-D search method is validated by showing that the optimal solution of the relaxed problem is rank-one. Simulation results demonstrate that the proposed SPCA method achieves the same performance as the scheme based on 1-D search method but with much lower complexity.
UR - http://www.scopus.com/inward/record.url?scp=85049171602&partnerID=8YFLogxK
U2 - 10.1109/WCNC.2018.8377223
DO - 10.1109/WCNC.2018.8377223
M3 - Conference contribution
AN - SCOPUS:85049171602
T3 - IEEE Wireless Communications and Networking Conference, WCNC
SP - 1
EP - 6
BT - 2018 IEEE Wireless Communications and Networking Conference, WCNC 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE Wireless Communications and Networking Conference, WCNC 2018
Y2 - 15 April 2018 through 18 April 2018
ER -