Performance Analysis of Physical Layer Security for Over-the-Air Computation Using Distributed Null-Steering Beamforming
Iqbal, Usman Cho, Sunghwan Jung, Haejoon Guizani, Mohsen
Iqbal, Usman
Cho, Sunghwan
Jung, Haejoon
Guizani, Mohsen
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Department
Machine Learning
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Type
Journal article
Date
2025
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Language
English
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Abstract
Over-the-air computation (AirComp) reduces the latency of wireless data aggregation by leveraging the superposition property of the wireless channel to achieve the desired function. This letter proposes a physical layer security (PLS) technique based on cooperative beamforming (CB) and distributed null steering for an AirComp network to effectively prevent eavesdropping. We provide a theoretical framework to combine CB and AirComp with adaptive null steering to degrade the reception of an eavesdropper located near the legitimate receiver. A closed-form expression for the average mean squared error (MSE) is derived, showing that the proposed distributed null-steering beamforming provides significantly better PLS performance than analog cooperative beamforming. Furthermore, a genetic algorithm is employed to jointly optimize the nulling factor and the direction to maximize the average MSE gap.
Citation
A. Kareem, J. Lahoud, and H. Cholakkal, “PARIS3D: Reasoning-Based 3D Part Segmentation Using Large Multimodal Model,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) , vol. 15130, pp. 466–482, Jan. 2025, doi: 10.1007/978-3-031-73220-1_27.
Source
IEEE Communications Letters
Conference
Keywords
distributed null steering, mean-squared error, Over-the-air computation, physical layer security
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Source
Publisher
IEEE