Secrecy Capacity Maximization for IRS-Assisted High-Speed Train Communications

In this letter, we propose an IRS-assisted MIMO communication system model in the presence of an eavesdropper (Eve). A distance-dependent Rician factor and real-time Doppler frequency offset (DFO) compensation mechanism are utilized to characterize highly time-varying wireless channels. The secrecy...

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Vydané v:IEEE communications letters Ročník 29; číslo 6; s. 1290 - 1294
Hlavní autori: Li, Cuiran, Luan, Jiahui, Zhang, Zepeng, Ai, Bo, Wu, Hao, Xie, Jianli
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York IEEE 01.06.2025
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Algorithms
Array signal processing
Beamforming
Communication system security
Communications systems
Convexity
Doppler effect
High speed rail
high-speed rail (HSR) communications
Intelligent reflecting surface (IRS)
Iron
Long short term memory
MIMO communication
Optimization
Real time
Rician channels
secrecy capacity
Simulation
Transmitting antennas
Vectors
Wireless communication
ISSN:1089-7798, 1558-2558
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Popis
Shrnutí:In this letter, we propose an IRS-assisted MIMO communication system model in the presence of an eavesdropper (Eve). A distance-dependent Rician factor and real-time Doppler frequency offset (DFO) compensation mechanism are utilized to characterize highly time-varying wireless channels. The secrecy capacity optimization problem is formulated by jointly optimizing the transmit beamforming, artificial noise (AN) matrix, and IRS phase shifts, subject to transmit power and unit modulus constraints. To solve the non-convex problem, it is transformed into convex optimization problem by using weighted minimum mean square error (WMMSE) algorithm, and an alternating optimization strategy with coupled variables is used to derive the optimal solution. Simulation results show that the optimization algorithm proposed in this letter converges quickly and achieves higher secrecy capacity.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1089-7798
1558-2558
DOI:10.1109/LCOMM.2025.3559484