期刊
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
卷 20, 期 4, 页码 2487-2501出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TWC.2020.3042828
关键词
Wireless communication; Array signal processing; Transmitters; Simulation; Channel estimation; Probability; Optimization; Intelligent reflecting surface (IRS); reconfigurable intelligent surface (RIS); robust design; imperfect CSI; physical layer security; secure communications
资金
- National Natural Science Foundation of China [61661032]
- Young Natural Science Foundation of Jiangxi Province [20181BAB202002]
- China Postdoctoral Science Foundation [2017M622102]
- Foundation from China Scholarship Council [201906825071]
- EPSRC [EP/R006466/1]
- EPSRC [EP/R006466/1] Funding Source: UKRI
This paper investigates the design of robust and secure transmission in intelligent reflecting surface (IRS) aided wireless communication systems. The proposed scheme significantly reduces the transmit power compared to other benchmark schemes by jointly optimizing the beamforming vector, the artificial noise covariance matrix, and the IRS phase shifts. The simulation results demonstrate the effectiveness of the proposed method in minimizing the transmit power.
In this paper, we investigate the design of robust and secure transmission in intelligent reflecting surface (IRS) aided wireless communication systems. In particular, a multi-antenna access point (AP) communicates with a single-antenna legitimate receiver in the presence of multiple single-antenna eavesdroppers, where the artificial noise (AN) is transmitted to enhance the security performance. Besides, we assume that the cascaded AP-IRS-user channels are imperfect due to the channel estimation error. To minimize the transmit power, the beamforming vector at the transmitter, the AN covariance matrix, and the IRS phase shifts are jointly optimized subject to the outage rate probability constraints under the statistical cascaded channel state information (CSI) error model. To handle the resulting non-convex optimization problem, we first approximate the outage rate probability constraints by using the Bernstein-type inequality. Then, we develop a suboptimal algorithm based on alternating optimization, the penalty-based and semidefinite relaxation methods. Simulation results reveal that the proposed scheme significantly reduces the transmit power compared to other benchmark schemes.
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