Space-Time Adaptive Beamforming for Satellite Communications: Harnessing Doppler as New Signaling Dimensions

TL;DR

This paper introduces space-time adaptive beamforming (STAB) that uses Doppler shifts as an additional signaling dimension to improve multiuser communication in dense LEO satellite downlinks, overcoming spatial multiplexing limitations.

Contribution

The paper characterizes the limitations of spatial multiplexing in LEO satellite channels and proposes STAB with a Doppler-based user selection algorithm to enhance sum rates.

Findings

STAB restores sum rate where zero-forcing fails.

Doppler shifts serve as an effective discrimination dimension.

Numerical results show significant sum rate improvements.

Abstract

Low Earth orbit (LEO) satellite downlinks are fundamentally limited by severe channel correlation: the line-of-sight (LoS)-dominant propagation and high orbital altitude confine users to a narrow angular region, rendering the multiuser channel matrix ill-conditioned. This paper provides a rigorous characterization of this limitation by exploiting the Vandermonde structure of the channel. Specifically, we link the minimum eigenvalue of the channel Gram matrix to user crowding through a balls-and-bins abstraction, and derive asymptotic sum rate scaling laws for both uniform linear arrays and uniform planar arrays. Our analysis reveals a sharp density threshold beyond which zero-forcing (ZF) precoding provably fails. To overcome this spatial multiplexing breakdown, we propose space-time adaptive beamforming (STAB), which exploits user-dependent residual Doppler shifts as an additional discrimination dimension. By constructing a time-extended channel in the joint space-Doppler domain, STAB restores a non-vanishing sum rate in regimes where purely spatial ZF collapses. We further develop a space-Doppler user selection (SDS) algorithm that leverages both spatial and Doppler separability for scheduling. Numerical results corroborate the analytical predictions and demonstrate that STAB with SDS achieves substantial sum rate gains over conventional methods in dense LEO downlink scenarios.