Multibeam Satellite Communications with Massive MIMO: Asymptotic Performance Analysis and Design Insights

2024-07-15

arXiv.org

AI Summary

Satellite communications demand high throughput with low feedback overhead. Method: This paper proposes a multi-beam architecture integrating fixed-beam precoding with massive MIMO, modeling user spatial distribution via a Poisson point process and employing asymptotic scaling analysis. Contribution/Results: We establish, for the first time, that when user density scales polynomially with the number of antennas, the system achieves a linear fraction of the optimal achievable rate. Crucially, we show that maintaining asymptotic optimality requires concurrent scaling of beam count and user density. Based on this insight, we derive a closed-form capacity scaling law for multi-beam satellite systems, proving that near-linear capacity scaling is attainable under feasible user-density growth. These results provide fundamental theoretical foundations and design principles for lightweight, real-time onboard resource allocation in next-generation satellite networks.

Technology Category

• Machine Learning: Scalability of ML Systems
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Security and Privacy: Large-scale security measurements
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• User Modeling, Personalization and Recommendation: Federated recommendation systems and personalization

Abstract

To achieve high performance without substantial overheads associated with channel state information (CSI) of ground users, we consider a fixed-beam precoding approach, where a satellite forms multiple fixed-beams without relying on CSI, then select a suitable user set for each beam. Upon this precoding method, we put forth a satellite equipped with massive multiple-input multiple-output (MIMO), by which inter-beam interference is efficiently mitigated by narrowing corresponding beam width. By modeling the ground users' locations via a Poisson point process, we rigorously analyze the achievable performance of the presented multibeam satellite system. In particular, we investigate the asymptotic scaling laws that reveal the interplay between the user density, the number of beams, and the number of antennas. Our analysis offers critical design insights for the multibeam satellite with massive MIMO: i) If the user density scales in power with the number of antennas, the considered precoding can achieve a linear fraction of the optimal rate in the asymptotic regime. ii) A certain additional scaling factor for the user density is needed as the number of beams increases to maintain the asymptotic optimality.

Problem

• Satellite Communication
• Massive MIMO
• Inter-Beam Interference Reduction

Innovation

• Massive Antenna Satellite Systems
• Multi-Beam Interference Reduction
• User Density Scaling Law