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Beamforming and Jamming Optimization for IRS-Aided Secure NOMA Networks

The integration of intelligent reflecting surface (IRS) and multiple access provides a promising solution to improved coverage and massive connections at low cost. However, securing IRS-aided networks remains a challenge since the potential eavesdropper also has access to an additional IRS reflectio...

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Published in:IEEE transactions on wireless communications 2022-03, Vol.21 (3), p.1557-1569
Main Authors: Wang, Wei, Liu, Xin, Tang, Jie, Zhao, Nan, Chen, Yunfei, Ding, Zhiguo, Wang, Xianbin
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cited_by cdi_FETCH-LOGICAL-c333t-ad211998be96669a515ada74b58d3e26e0b71531b772e8cf14ad5f689c8459a63
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creator Wang, Wei
Liu, Xin
Tang, Jie
Zhao, Nan
Chen, Yunfei
Ding, Zhiguo
Wang, Xianbin
description The integration of intelligent reflecting surface (IRS) and multiple access provides a promising solution to improved coverage and massive connections at low cost. However, securing IRS-aided networks remains a challenge since the potential eavesdropper also has access to an additional IRS reflection link, especially when the eavesdropping channel state information is unknown. In this paper, we propose an IRS-assisted non-orthogonal multiple access (NOMA) scheme to achieve secure communication via artificial jamming, where the multi-antenna base station sends the NOMA and jamming signals together to the legitimate users with the assistance of IRS, in the presence of a passive eavesdropper. The sum rate of legitimate users is maximized by optimizing the transmit beamforming, the jamming vector and the IRS reflecting vector, satisfying the quality of service requirement, the IRS reflecting constraint and the successive interference cancellation (SIC) decoding condition. In addition, the received jamming power is adapted at the highest level at all legitimate users for successful cancellation via SIC. To tackle this non-convex optimization problem, we first decompose it into two subproblems, and then each subproblem is converted into a convex one using successive convex approximation. An alternate optimization algorithm is proposed to solve them iteratively. Numerical results show that the secure transmission in the proposed IRS-NOMA scheme can be effectively guaranteed with the assistance of artificial jamming.
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subjects Algorithms
Array signal processing
Artificial jamming
Beamforming
beamforming optimization
Computational geometry
Convexity
Eavesdropping
intelligent reflecting surface
Jamming
NOMA
non-orthogonal multiple access
Nonorthogonal multiple access
Optimization
physical layer security
Receivers
Silicon carbide
Wireless communication
title Beamforming and Jamming Optimization for IRS-Aided Secure NOMA Networks
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