Multi-Satellite Cooperative MIMO Transmission: Statistical CSI-Aware RSMA Precoding Design

2025-08-14

AI Summary

In low-Earth-orbit (LEO) satellite systems, the acquisition of instantaneous channel state information (iCSI) is severely hindered by long propagation delays and strong Doppler shifts, thereby limiting the performance of cooperative MIMO. To address this, we propose a rate-splitting multiple access (RSMA) precoding framework leveraging statistical CSI (sCSI) only. Our method integrates statistical channel modeling, weighted minimum mean-square error (WMMSE) optimization, and robust precoding design—enabling inter-satellite coordinated transmission without requiring real-time iCSI feedback. Simulation results demonstrate that the proposed scheme achieves spectral efficiency and user fairness close to the ideal iCSI-based benchmark, while substantially outperforming conventional space-division multiple access (SDMA). It thus establishes a deployable, low-overhead, high-performance cooperative communication paradigm for highly dynamic LEO constellations.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Machine Learning: Large Multimodal Models (LMMs)
• Multiagent Systems: Coordination and Collaboration

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• Security and Privacy: Large-scale security measurements
• Search and Retrieval-Augmented AI: Large language models for search

Abstract

We investigate inter-satellite cooperative transmission in a multiple low-Earth orbit (LEO) satellite communication system to enhance spectral efficiency. Specifically, we design multiple-input multipleoutput (MIMO) precoding at LEO satellites for cooperative rate-splitting multiple access (RSMA). Given the difficulty of acquiring instantaneous channel state information (iCSI) due to long delays and Doppler effects, we formulate an ergodic max-min fairness rate (MMFR) maximization problem based on statistical CSI (sCSI). To address the challenge of ergodic rate evaluation, we approximate the problem using closed-form upper bounds and develop a weighted minimum mean squared error-based algorithm to obtain a stationary point. Simulation results demonstrate that the proposed sCSI-based RSMA scheme approaches iCSI-based performance and significantly outperforms conventional space-division multiple access.

Problem

• Enhance spectral efficiency in multi-satellite cooperative MIMO transmission
• Design RSMA precoding using statistical CSI due to iCSI challenges
• Propose sCSI-based algorithm to approach iCSI performance benchmarks

Innovation

• Uses statistical CSI for RSMA precoding
• Approximates ergodic rates with upper bounds
• Develops WMMSE-based stationary point algorithm