Robust Secure Communication for Health Care IoT system with Statistical Channel Uncertainties

With the increasing number of mobile devices, the internet of things (IoT) has spread widely in all aspects of your life. Health-loT (H-IoT) is one of the most evolving applications, from health monitoring services to remote health care. Due to the physical vulnerability of the wireless IoT networks and the limited computational complexity of the sensors node, researchers have paid particular attention to energy-efficient physical layer security. In this paper, we propose a robust, secure SWIPT based joint beamforming algorithm for a multi-user H-IoT system in the presence of eavesdroppers. We formulate an optimization problem of optimizing the secrecy rate of the system by collectively optimizing the beamforming vector and power splitting ratios while satisfying the signal to interference noise (SINR) ratio and energy harvesting ration constraint of each legitimate user. The formulated problem also considered the use of additional noise to enhance secure communication. A solution based on Bernstein's equality is presented since the optimization problem is non-convex due to the probabilistic constraints. It is evident from the simulation results that the proposed algorithm performs much better than the S-procedure algorithm.