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

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.