Enabling Scalable Distributed Beamforming via Networked LEO Satellites Towards 6G

TL;DR

This paper introduces scalable distributed beamforming schemes for LEO satellite networks using statistical channel information, achieving near-centralized performance and outperforming baseline methods in sum rate.

Contribution

It proposes novel decentralized beamforming algorithms for LEO satellite networks that are scalable, effective, and based on statistical channel information, with performance close to centralized solutions.

Findings

Distributed schemes achieve near-centralized sum rate performance.

The proposed methods outperform simple beamformers and single-satellite baselines.

Trade-offs between delay and overhead are characterized for different topologies.

Abstract

In this paper, we propose scalable distributed beamforming schemes over low Earth orbit (LEO) satellite networks that rely solely on statistical channel state information for downlink orthogonal frequency division multiplexing systems. We begin by introducing the system model and presenting a pragmatic yet effective analog beamformer and user-scheduling design. We then derive a closed-form lower bound on the ergodic sum rate, based on the hardening bound, for the digital beamformer design. Next, we formulate a per-satellite power-constrained sum-rate maximization problem, whose centralized solution, obtained via the weighted minimum mean squared error (WMMSE) framework, establishes performance limits and motivates decentralized strategies. We subsequently introduce two decentralized optimization schemes, based on approximating the hardening bound and decentralizing the WMMSE framework, for representative inter-satellite link topologies. In the Ring scheme, satellites update beamformers locally and exchange intermediate parameters sequentially. In the Star scheme, edge satellites update beamformers locally and in parallel, achieving consensus on intermediate parameters at a central satellite using a penalty-dual decomposition framework. Extensive simulations demonstrate that our distributed designs achieve near-centralized performance with superior scalability, substantially outperforming simple closed-form beamformers and single-satellite baselines in sum rate. Additionally, the delay-overhead trade-off between the two topologies is revealed.