@inproceedings{4576a70f06804c8090863e8d2df369a9,
title = "IRS-Enhanced Spectrum Sensing and Secure Transmission in CRNs: Secrecy Rate Maximization",
abstract = "Spectrum sensing and the communication security are of crucial importance in cognitive radio networks (CRNs). In this paper, intelligent reflecting surface (IRS) is exploited in CRNs to simultaneously enhance the spectrum sensing accuracy and the secure performance achieved by using physical layer security (PLS) techniques. The sum secrecy rate of the secondary users (SUs) is maximized by jointly optimizing the sensing time, the beamforming design and the IRS phase shifts. A safe approximation is adopted to transform the probability of detection into a tractable expression. A computationally efficient block coordinate descent (BCD)-based algorithm with the techniques of successive convex approximation (SCA) and semidefinite relaxation (SDR) is exploited to optimize the beamforming and the phase shifts alternately. Simulation results demonstrate that our proposed algorithm can significantly improve both the sensing performance and the secrecy rate compared with the benchmark schemes.",
author = "Zi Wang and Wei Wu and Fuhui Zhou and Baoyun Wang and Qihui Wu and Quek, {Tony Q.S.}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 IEEE International Conference on Communications, ICC 2023 ; Conference date: 28-05-2023 Through 01-06-2023",
year = "2023",
doi = "10.1109/ICC45041.2023.10279590",
language = "English",
series = "IEEE International Conference on Communications",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "2382--2387",
editor = "Michele Zorzi and Meixia Tao and Walid Saad",
booktitle = "ICC 2023 - IEEE International Conference on Communications",
address = "United States",
}