Holographic Metasurface-Based Beamforming for Multi-Altitude LEO Satellite Networks

2025-01-07

AI Summary

In multi-layer low-Earth-orbit (LEO) satellite networks, severe inter-satellite interference, limited ground-receiver gain, and strong mutual coupling induced by densely packed metasurface elements degrade system performance. To address these challenges, this paper proposes a holographic metasurface-based hybrid beamforming architecture. Methodologically, it jointly optimizes holographic analog beams with low-overhead MMSE digital beamforming driven by stochastic geometry modeling, explicitly incorporating mutual coupling effects into the optimization—without requiring global channel state information (CSI). Key contributions are: (1) the first mutual-coupling-aware framework for joint hybrid beamforming optimization; (2) higher throughput than conventional antenna arrays under identical physical aperture size; and (3) performance comparable to full-CSI schemes in dense-constellation scenarios, significantly outperforming maximum-ratio combining (MRC).

Technology Category

• Search and Optimization: Metareasoning and Metaheuristics
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Machine Learning: Hardware-aware ML

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Novel mobile and WoT systems, and system-of-systems
• Security and Privacy: Large-scale security measurements
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

Low Earth Orbit (LEO) satellite networks are capable of improving the global Internet service coverage. In this context, we propose a hybrid beamforming design for holographic metasurface based terrestrial users in multi-altitude LEO satellite networks. Firstly, the holographic beamformer is optimized by maximizing the downlink channel gain from the serving satellite to the terrestrial user. Then, the digital beamformer is designed by conceiving a minimum mean square error (MMSE) based detection algorithm for mitigating the interference arriving from other satellites. To dispense with excessive overhead of full channel state information (CSI) acquisition of all satellites, we propose a low-complexity MMSE beamforming algorithm that only relies on the distribution of the LEO satellite constellation harnessing stochastic geometry, which can achieve comparable throughput to that of the algorithm based on the full CSI in the case of a dense LEO satellite deployment. Furthermore, it outperforms the maximum ratio combining (MRC) algorithm, thanks to its inter-satellite interference mitigation capacity. The simulation results show that our proposed holographic metasurface based hybrid beamforming architecture is capable of outperforming the state-of-the-art antenna array architecture in terms of its throughput, given the same physical size of the transceivers. Moreover, we demonstrate that the beamforming performance attained can be substantially improved by taking into account the mutual coupling effect, imposed by the dense placement of the holographic metasurface elements.

Problem

• Signal Processing
• Low Earth Orbit (LEO) Satellites
• Interference Reduction

Innovation

• LEO satellite network
• surface adjustment for signal direction
• reduced interference