Cooperative IRS and IOS-Aided Finite Blocklength Covert Communications in NOMA Networks
Li, Qiang Xu, Dongyang Liu, Lei Du, Jianbo Niyato, Dusit Guizani, Mohsen
Li, Qiang
Xu, Dongyang
Liu, Lei
Du, Jianbo
Niyato, Dusit
Guizani, Mohsen
Supervisor
Department
Machine Learning
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Type
Journal article
Date
2025
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Language
English
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Abstract
This paper proposes a finite blocklength covert non-orthogonal multiple access (NOMA) communication scheme based on cooperative intelligent reflecting surfaces (IRS) and intelligent omni-surfaces (IOS). To achieve covert transmission in the NOMA network, in the proposed scheme, the IRS switches between the IRS and IOS mechanisms to create uncertainty. To analyze the performance of this scheme, we first characterize the statistical properties of the users' cascaded channels. Then, we derive the closed-form expressions of the expectation of the Kullback-Leibler (KL) divergence and the average block error rates (BLERs) of NOMA users. To balance covertness and reliability, we formulate an optimization problem to maximize the effective covert throughput (ECT) subject to the reliability and delay constraints and the level of covertness. Via this optimization, we then obtain closed-form expressions for optimal power and blocklength. Simulation results demonstrate that the ECT of the proposed scheme is much higher than that of benchmarks.
Citation
Q. Li, D. Xu, L. Liu, J. Du, D. Niyato, and M. Guizani, “Cooperative IRS and IOS-Aided Finite Blocklength Covert Communications in NOMA Networks,” IEEE Trans Veh Technol, 2024, doi: 10.1109/TVT.2024.3472108.
Source
IEEE Transactions on Vehicular Technology
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Keywords
Covert communications, Finite Blocklength, Intelligent Reflecting/omni-surfaces (IRS/IOS), NOMA
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Publisher
IEEE