Space-Time Adaptive Beamforming for Satellite Communications: Harnessing Doppler as New Signaling Dimensions
arXiv:2603.29359v1 Announce Type: new 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 mul
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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.
Comments: 13 pages, 7 figures
Subjects:
Signal Processing (eess.SP)
Cite as: arXiv:2603.29359 [eess.SP]
(or arXiv:2603.29359v1 [eess.SP] for this version)
https://doi.org/10.48550/arXiv.2603.29359
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Hyeongtak Yun [view email] [v1] Tue, 31 Mar 2026 07:29:30 UTC (1,491 KB)
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