Intelligent Reflecting Surface for Wireless Communication Security and Privacy
Shihao Yan, Xiaobo Zhou, Derrick Wing Kwan Ng, Jinhong Yuan, and, Naofal Al-Dhahir

TL;DR
This paper explores how intelligent reflecting surfaces (IRS) can enhance wireless security and privacy by improving secrecy rates, enabling covert communications, and creating transmission randomness, while addressing challenges like optimal amplitude design and CSI estimation.
Contribution
It introduces new insights into IRS-based physical layer security and covert communications, including amplitude optimization, tradeoffs with CSI accuracy, and a deep learning-based channel estimation method.
Findings
Optimal IRS element amplitudes vary and are not always 1.
Tradeoff exists between secrecy performance and CSI estimation accuracy.
Deep neural network-based channel estimation can improve covert communication rates.
Abstract
Intelligent reflection surface (IRS) is emerging as a promising technique for future wireless communications. Considering its excellent capability in customizing the channel conditions via energy-focusing and energy-nulling, it is an ideal technique for enhancing wireless communication security and privacy, through the theories of physical layer security and covert communications, respectively. In this article, we first present some results on applying IRS to improve the average secrecy rate in wiretap channels, to enable perfect communication covertness, and to deliberately create extra randomness in wireless propagations for hiding active wireless transmissions. Then, we identify multiple challenges for future research to fully unlock the benefits offered by IRS in the context of physical layer security and covert communications. With the aid of extensive numerical studies, we…
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Taxonomy
TopicsAdvanced Wireless Communication Technologies · Satellite Communication Systems · Telecommunications and Broadcasting Technologies
