Joint Device Selection and Power Control for Energy Sustainable RIS-NOMA-Enhanced Wireless IoT Networks

Xing Hao, Ziru Chen, Lin Cai, Haibo Zhou, Tom H. Luan

Abstract: In this article, we consider an energy sustainable wireless Internet of Things (IoTs) network with a reconfigurable intelligent surface (RIS). Specifically, the hybrid access point (HAP) performs beamforming to transfer energy to a set of devices, and the devices then use the harvested energy for Nonorthogonal multiple access (NOMA)-based data transmissions, where a RIS is employed to enhance both the energy harvesting and data transmissions. An optimization problem is formulated to maximize the sum-rate of IoT devices by jointly optimizing the energy beamforming of the HAP, the phase shifts of RIS, the selection of devices in NOMA transmissions with power control, and the time allocation for energy harvesting. As the formulated optimization problem is a complex mixed-integer nonlinear programming (MNLP) problem, we decompose it into four subproblems and apply block coordinate descent (BCD) to iteratively optimize each subproblem until convergence is achieved. A novel joint optimization algorithm is proposed to select a subset of devices with transmission power control to attain the maximum sum-rate. A closed-form expression for the optimal time allocation is further derived to strike a balance between the energy harvesting and the data transmissions, considering the residual energy resulting from the previous power control. Simulations validate that the proposed solution outperforms state-of-the-art algorithms in the literature.

External IDs:dblp:journals/iotj/HaoCCZL25