2025/06/02 by Tareq Y. Al-Naffouri, Zhang, Yuchen, Al-Naffouri, Tareq Y. · 2 citations
Engineering · #Advanced MIMO Systems Optimization #FOS: Electrical engineering #IoT Networks and Protocols #Satellite Communication Systems #Signal Processing (eess.SP) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2506.01382
openalex publication_date 2025/06/02 · openalex created_date 2025/10/07 · openalex updated_date 2026/07/29
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.