Journal
IEEE TRANSACTIONS ON COMMUNICATIONS
Volume 69, Issue 8, Pages 5394-5408Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCOMM.2021.3082779
Keywords
Array signal processing; Optimization; MIMO communication; MISO communication; Symmetric matrices; Silicon; Signal to noise ratio; Covert transmission; imperfect CSI; intelligent reflecting surface (IRS); joint beamforming and phase shift optimization
Funding
- Key Project of National Natural Science Foundation of China [61631015, 61971337, 61901328, 61941118]
- National Natural Science Foundation [61825104]
- Key Laboratory Project of China Electronic Science and Technology Group [CLDL-20182410]
- Fundamental Research Funds for the Central Universities [XJS210109]
- Technology Innovation Plan [2019921815KYPT009JC011]
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The study focuses on covert transmission in an intelligent reflecting surface (IRS) aided communication system, optimizing transmission power and phase shift to maximize covert transmission rate. Various algorithms are proposed to solve the optimization problem and simulations are performed to verify the results. The numerical results indicate that IRS can degrade the covert transmission rate when the warden is closer to the IRS than the intended receiver.
Covert transmission is studied for an intelligent reflecting surface (IRS) aided communication system, where Alice aims to transmit messages to Bob without being detected by the warden Willie. Specifically, an IRS is used to increase the data rate at Bob under a covert constraint. For the considered model, when Alice is equipped with a single antenna, the transmission power at Alice and phase shift at the IRS are jointly optimized to maximize the covert transmission rate with either instantaneous or partial channel state information (CSI) of Willie's link. In addition, when multiple antennas are deployed at Alice, we formulate a joint transmit beamforming and IRS phase shift optimization problem to maximize the covert transmission rate. One local optimal algorithm and two low-complexity suboptimal algorithms are proposed to solve the problem. Furthermore, for the case of imperfect CSI of Willie's link, the optimization problem is reformulated by using the triangle and Cauchy-Schwarz inequalities. The reformulated optimization problems are solved using an alternative algorithm, semidefinite relaxation (SDR) and Gaussian randomization techniques. Finally, simulations are performed to verify our analysis. The numerical results show that an IRS can degrade the covert transmission rate when Willie is closer to the IRS than Bob.
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