Efficient Two-Timescale User Grouping and Resource Allocation for LEO Satellite Networks With Uneven Traffic

Abstract

Low Earth Orbit (LEO) satellite networks are envisioned to provide wide-area connectivity for a massive number of user terminals. Realizing this vision requires efficient resource allocation, including user grouping, beamforming (BF) and power control, that adapts to the uneven spatio-temporal distribution of user location and traffic demand. Existing allocation schemes primarily rely on channel state information (CSI) while neglecting the stochastic nature of traffic arrivals, leading to spectrum efficiency degradation and reduced system stability. To solve this problem, we propose a two-timescale joint optimization framework that integrates CSI and queue state information (QSI) to enable efficient resource allocation for LEO satellite systems. On the slow timescale, we propose a novel two-stage user grouping scheme that combines traffic-aware K-means++ clustering with a grid-based spatial dividing method to construct user groups with traffic-aware load characteristics and improved spatial orthogonality. These pre-constructed groups serve as scheduling candidates for the fast timescale, enabling structured decisions with reduced complexity and improved spatial separability among co-scheduled users. On the fast timescale, we develop a queue-aware group scheduling, BF, and power control algorithm based on the CSI and QSI, aiming to maximize queue-weighted utility under signal-to-interference-plus-noise ratio and power constraints. Finally, simulation results verify that the proposed approach significantly improves system service performance while ensuring queue stability, outperforming existing benchmark methods.