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

doi:10.1109/TIFS.2024.3486548

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

2024-01-01

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DOI：10.1109/TIFS.2024.3486548

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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.

Keywords:

Transmitters

Receivers

Precoding

Eavesdropping

Wireless networks

Surveillance

Oral communication

Forensics

Integrated circuit modeling

Interference channels

Physical layer security

robust optimization

artificial noise

distributed precoding

MIMO

interference channel

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

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