Secure Beamforming for Integrated Sensing, NOMA Communication, and Over-the-Air Computation Networks

With the rapid evolution of wireless technologies, the deep integration of sensing, communication and computation has heralded a novel and promising paradigm. In this paper, we propose a secure beamforming design framework for integrated sensing, non-orthogonal multiple access (NOMA) communication and over-the-air computation (AirComp) networks, which can provide multi-functional intelligent services for communication-intensive, computation-intensive, delay-sensitive and security-sensitive applications. In the considered network, each dual-functional intelligent device engages in NOMA information transmission and AirComp. Meanwhile, the triple-functional base station conducts target sensing, NOMA signal decoding and data aggregation simultaneously. Our aim is to maximize the sum secrecy rate (SSR) of NOAM devices while ensuring that the quality of service requirements for both sensing and AirComp are met within the transmit power constraints imposed on all nodes. The formulated optimization problem involves coupled variables and logarithmic determinant, thus it is highly non-convex. To solve it, we propose an efficient matrix-extended generalized Lagrangian dual transformation based algorithm with penalty method, which can obtain the Karush-Kuhn-Tucker (KKT) solution to the original problem with low-complexity and convergence guarantee. Additionally, the well-known successive convex approximation based algorithm is also employed to address the formulated SSR maximization problem. However, its computational complexity significantly exceeds that of our proposed algorithm. Finally, extensive experiments demonstrate the performance improvement of our proposal compared with the benchmark approaches.

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Publication Details

Journal
IEEE Transactions on Information Forensics and Security
Published
2025-01-01
DOI
https://doi.org/10.1109/tifs.2025.3614008
Citations
2
Primary Topic
Wireless Body Area Networks
Type
article
Field-Weighted Citation Impact
1.35
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article

Secure Beamforming for Integrated Sensing, NOMA Communication, and Over-the-Air Computation Networks

Quanzhong Li, Changjie Hu, Qi Zhang, Qiang Li
2 citations
IEEE Transactions on Information Forensics and Security
Wireless Body Area Networks
1.35
article

Secure Beamforming for Integrated Sensing, NOMA Communication, and Over-the-Air Computation Networks

Quanzhong Li, Changjie Hu, Qi Zhang, Qiang Li
article en
2 citations

Abstract

With the rapid evolution of wireless technologies, the deep integration of sensing, communication and computation has heralded a novel and promising paradigm. In this paper, we propose a secure beamforming design framework for integrated sensing, non-orthogonal multiple access (NOMA) communication and over-the-air computation (AirComp) networks, which can provide multi-functional intelligent services for communication-intensive, computation-intensive, delay-sensitive and security-sensitive applications. In the considered network, each dual-functional intelligent device engages in NOMA information transmission and AirComp. Meanwhile, the triple-functional base station conducts target sensing, NOMA signal decoding and data aggregation simultaneously. Our aim is to maximize the sum secrecy rate (SSR) of NOAM devices while ensuring that the quality of service requirements for both sensing and AirComp are met within the transmit power constraints imposed on all nodes. The formulated optimization problem involves coupled variables and logarithmic determinant, thus it is highly non-convex. To solve it, we propose an efficient matrix-extended generalized Lagrangian dual transformation based algorithm with penalty method, which can obtain the Karush-Kuhn-Tucker (KKT) solution to the original problem with low-complexity and convergence guarantee. Additionally, the well-known successive convex approximation based algorithm is also employed to address the formulated SSR maximization problem. However, its computational complexity significantly exceeds that of our proposed algorithm. Finally, extensive experiments demonstrate the performance improvement of our proposal compared with the benchmark approaches.

IEEE Transactions on Information Forensics and SecurityVol. 20
Sun Yat-sen University (CN), Peng Cheng Laboratory (CN)
Openalex Percentile: Top 17%
Wireless Body Area Networks
1.35
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