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Distributed Robust Artificial-Noise-Aided Secure Precoding for Wiretap MIMO Interference Channels

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  • Zhengmin Kong
  • Jing Song
  • Shaoshi Yang
  • Li Gan
  • Weizhi Meng
  • Tao Huang
  • Sheng Chen
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<mark>Journal publication date</mark>7/11/2024
<mark>Journal</mark>IEEE Transactions on Information Forensics and Security
Volume19
Number of pages11
Pages (from-to)10130-10140
Publication StatusPublished
Early online date25/10/24
<mark>Original language</mark>English

Abstract

We propose a distributed artificial noise-assisted precoding scheme for secure communications over wiretap multi-input multi-output (MIMO) interference channels, where K legitimate transmitter-receiver pairs communicate in the presence of a sophisticated eavesdropper having more receive-antennas than the legitimate user. Realistic constraints are considered by imposing statistical error bounds for the channel state information of both the eavesdropping and interference channels. Based on the asynchronous distributed pricing model, the proposed scheme maximizes the total utility of all the users, where each user’s utility function is defined as the secrecy rate minus the interference cost imposed on other users. Using the weighted minimum mean square error, Schur complement and sign-definiteness techniques, the original non-concave optimization problem is approximated with high accuracy as a quasi-concave problem, which can be solved by the alternating convex search method. Simulation results consolidate our theoretical analysis and show that the proposed scheme outperforms the artificial noise-assisted interference alignment and minimum total mean-square error-based schemes.