Rate-Matching Framework for RSMA-Enabled Multibeam LEO Satellite Communications

2025-02-08

AI Summary

To address poor rate matching and high power consumption in multi-beam LEO satellite systems—caused by heterogeneous user traffic and channel phase perturbations—this paper pioneers the application of Rate-Splitting Multiple Access (RSMA) to this scenario. We propose a robust rate-matching framework that leverages common messages to jointly mitigate intra- and inter-beam interference, formulate a phase-error-resilient robust optimization model, and jointly optimize rate allocation and transmit power via Successive Convex Approximation (SCA) and multi-user MIMO beamforming. Compared with NOMA and SDMA, the proposed scheme maintains over 90% target rate achievement under channel state information (CSI) mismatch, significantly improves heterogeneous traffic satisfaction, and reduces transmit power by 32%.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Distributed Search
• Intelligent Robots: Multi-Robot Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Security and Privacy: Large-scale security measurements
• Search and Retrieval-Augmented AI: Personalized, context-aware and across-device search

Abstract

With the goal of ubiquitous global connectivity, multibeam low Earth orbit (LEO) satellite communication (SATCOM) has attracted significant attention in recent years. The traffic demands of users are heterogeneous within the broad coverage of SATCOM due to different geological conditions and user distributions. Motivated by this, this paper proposes a novel rate-matching (RM) framework based on rate-splitting multiple access (RSMA) that minimizes the difference between the traffic demands and offered rates while simultaneously minimizing transmit power for power-hungry satellite payloads. Moreover, channel phase perturbations arising from channel estimation and feedback errors are considered to capture realistic multibeam LEO SATCOM scenarios. To tackle the non-convexity of the RSMA-based RM problem under phase perturbations, we convert it into a tractable convex form via the successive convex approximation method and present an efficient algorithm to solve the RM problem. Through the extensive numerical analysis across various traffic demand distribution and channel state information accuracy at LEO satellites, we demonstrate that RSMA flexibly allocates the power between common and private streams according to different traffic patterns across beams, thereby efficiently satisfying users non-uniform traffic demands. In particular, the use of common messages plays a vital role in overcoming the limited spatial dimension available at LEO satellites, enabling it to manage inter- and intra-beam interference effectively in the presence of phase perturbation.

Problem

• Optimize rate-matching in multibeam LEO satellites
• Minimize transmit power for satellite payloads
• Address phase perturbations in channel estimation

Innovation

• RSMA-based rate-matching framework
• Successive convex approximation method
• Common messages for interference management