Abstract
The integration of a near-space information network (NSIN) with the reconfigurable intelligent surface (RIS) is envisioned to significantly enhance the communication performance of future wireless communication systems by proactively altering wireless channels. This paper investigates the problem of deploying a RIS-integrated NSIN to provide energy-efficient, ultra-reliable and low-latency communications (URLLC) services for remote Internet of Things (IoT) devices. We mathematically formulate this problem as a resource optimization problem, aiming to maximize the effective throughput and minimize the system power consumption, subject to URLLC and physical resource constraints. We propose a joint resource allocation algorithm to solve this problem. In this algorithm, we discuss the optimization of phase shifts of RIS reflecting elements, derive an analysis-friendly expression of decoding error probability, and decompose the problem into two-layered optimization problems by analyzing the monotonicity, which makes the formulated problem analytically tractable. Simulation results show that the proposed algorithm is 34.14% more energy-efficient than diverse benchmark algorithms.