Harvested Power Fairness Optimization in MISO SWIPT Multicasting IoT with Individual Constraints

In this paper, we consider a Multiple Input Single Output (MISO) multicasting Internet of Things (IoT) system comprising of a multiantenna Transmitter (TX) that simultaneously transfers information and power to low power and data hungry IoT devices. Each IoT device is assumed to be equipped with Power Splitting (PS) hardware that enables Energy Harvesting (EH) and imposes an individual Quality of Service (QoS) constraint to the downlink communication. We study the joint design of TX precoding and IoT PS ratios for the considered MISO Simultaneous Wireless Information and Power Transfer (SWIPT) multicasting IoT with the objective of maximizing the minimum harvested energy among IoT, while satisfying their individual QoS requirements. In our novel EH fairness maximization formulation, we adopt a generic Radio Frequency (RF) EH model capturing practical rectification operation, and resulting in a nonconvex optimization problem. For this problem, we first present an equivalent Semi- Definite Relaxation (SDR) for the considered design problem and prove that it possesses unique global optimality. Then, capitalizing on our derived tight upper and lower bounds on the optimal solution, we present an efficient algorithmic implementation for the jointly optimal TX precoding and IoT PS ratio parameters. Insights on the optimal TX precoding structure are also presented. Representative numerical results including comparisons with benchmark schemes corroborate the usefulness of the proposed design and provide useful insights on the interplay of critical system parameters on the optimized power vs achievable rate trade off.