Robust Beamforming Designs in Secure MIMO SWIPT IoT Networks With a Nonlinear Channel Model

• Published in: IEEE internet of things journal Vol. 8; no. 3; pp. 1702 - 1715
• Main Authors: Zhu, Zhengyu, Wang, Ning, Hao, Wanming, Wang, Zhongyong, Lee, Inkyu
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.02.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Array signal processing; Beamforming; Communication system security; Complexity; Energy harvesting; Energy transfer; Internet of Things; Jamming; Noise generation; nonlinear energy harvesting; Optimization; physical-layer security; Power transfer; robust beamforming; Robustness; Search algorithms; Semidefinite programming; simultaneous wireless information and power transfer; Transmitters; Wireless communication; Wireless networks
• ISSN: 2327-4662; 2327-4662
• DOI: 10.1109/JIOT.2020.3014933

In this article, we study a robust beamforming design for multiuser multiple-input-multiple-output secrecy networks with simultaneous wireless information and power transfer (SWIPT). In this system, an access point, multiple Internet-of-Things (IoT) devices under the nonlinear energy harvesting (EH) model with a help of one cooperative jammer (CJ). We employ artificial noise (AN) generation to facilitate efficient wireless energy transfer and secure transmission. To achieve EH fairness, we aim to maximize the minimum harvested energy among users subject to secrecy rate constraint and total transmit power constraint in the presence of channel estimation errors. By incorporating a norm-bounded channel uncertainty model, the original robust problem is transformed into a two-layer optimization problem, where the inner layer problem is reformulated as semidefinite programming (SDP) and the outer layer problem is solved by a one-dimensional (1-D) line search algorithm. In addition, in order to reduce computational complexity, we propose an algorithm based on sequential parametric convex approximation (SPCA). Finally, simulation results show that the proposed SPCA method achieves the same performance as the two-layer algorithm with much lower complexity.