Robust Beamforming for Full-Duplex Integrated Secure Communication, Computation, and Energy Networks Under Imperfect CSI

Abstract

This paper proposes a robust beamforming framework for a full-duplex (FD) integrated secure communication, computation, and energy (ISC2E) network. In the considered network, an FD base station (BS) simultaneously performs downlink wireless power transfer while aggregating uplink over-the-air computation data and receiving confidential information. To mitigate physical layer security risks and sustain performance under imperfect channel state information (CSI), a robust artificial noise-aided joint beamforming strategy is proposed. Specifically, a worst-case optimization problem is formulated to maximize the achievable sum secrecy rate of the FD-BS. This formulation incorporates stringent quality-of-service constraints regarding worst-case computational mean squared error, energy harvesting, and legitimate communication rates, subject to bounded CSI errors. To address the mathematical intractability caused by non-convexity and semi-infinite constraints, a novel algorithm leveraging the cutting-set method (CSM) and extended matrix variable Lagrangian dual transformation (EMVLDT) is developed. The CSM iteratively discretizes the continuous uncertainty set, transforming the problem into tractable deterministic forms, which are subsequently solved via the proposed EMVLDT algorithm. Finally, simulation results demonstrate the superiority of our proposed algorithm over existing benchmarks and elucidate the critical trade-offs among secure communication, computation accuracy, and energy harvesting efficiency.