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http://dx.doi.org/10.3837/tiis.2022.10.003

Hybrid Resource Allocation Scheme in Secure Intelligent Reflecting Surface-Assisted IoT  

Su, Yumeng (College of Information and Communication Engineering, Harbin Engineering University)
Gao, Hongyuan (College of Information and Communication Engineering, Harbin Engineering University)
Zhang, Shibo (College of Information and Communication Engineering, Harbin Engineering University)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.16, no.10, 2022 , pp. 3256-3274 More about this Journal
Abstract
With the rapid development of information and communications technology, the construction of efficient, reliable, and safe Internet of Things (IoT) is an inevitable trend in order to meet high-quality demands for the forthcoming 6G communications. In this paper, we study a secure intelligent reflecting surface (IRS)-assisted IoT system where malicious eavesdropper trying to sniff out the desired information from the transmission links between the IRS and legitimate IoT devices. We discuss the system overall performance and propose a hybrid resource allocation scheme for maximizing the secrecy capacity and secrecy energy efficiency. In order to achieve the trade-off between transmission reliability, communication security, and energy efficiency, we develop a quantum-inspired marine predator algorithm (QMPA) for realizing rational configuration of system resources and prevent from eavesdropping. Simulation results demonstrate the superiority of the QMPA over other strategies. It is also indicated that proper IRS deployment and power allocation are beneficial for the enhancement of system overall capacity.
Keywords
Internet of Things; secure communications; intelligent reflecting surface; hybrid resource allocation; QMPA;
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