Supporting IoT With Rate-Splitting Multiple Access in Satellite and Aerial-Integrated Networks

• Published in: IEEE internet of things journal Vol. 8; no. 14; pp. 11123 - 11134
• Main Authors: Lin, Zhi, Lin, Min, de Cola, Tomaso, Wang, Jun-Bo, Zhu, Wei-Ping, Cheng, Julian
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 15.07.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Array signal processing; Cloud computing; Content delivery; Frequencies; Interference; Internet of Things; Internet of Things (IoT); multicast transmission; Multiple access; Optimization; Penalty function; rate-splitting multiple access (RSMA); satellite and aerial-integrated network (SAIN); Satellites; Splitting; Streaming media; Taylor series; Unmanned aerial vehicles
• ISSN: 2327-4662; 2327-4662
• DOI: 10.1109/JIOT.2021.3051603

To satisfy the explosive access demands of Internet-of-Things (IoT) devices, various kinds of multiple access techniques have received much attention. In this article, we investigate the multicast communication of a satellite and aerial-integrated network (SAIN) with rate-splitting multiple access (RSMA), where both satellite and unmanned aerial vehicle (UAV) components are controlled by network management center and operate in the same frequency band. Considering a content delivery scenario, the UAV subnetwork adopts the RSMA to support massive access of IoT devices (IoTDs) and achieve desired performances of interference suppression, spectral efficiency, and hardware complexity. We first formulate an optimization problem to maximize the sum rate of the considered system subject to the signal-interference-plus-noise-ratio requirements of IoTDs and per-antenna power constraints at the UAV and satellite. To solve this nonconvex optimization problem, we exploit the sequential convex approximation and the first-order Taylor expansion to convert the original optimization problem into a solvable one with the rank-one constraint, and then propose an iterative penalty function-based algorithm to solve it. Finally, simulation results verify that the proposed method can effectively suppress the mutual interference and improve the system sum rate compared to the benchmark schemes.