# Beam Management in Low Earth Orbit Satellite Networks with Random Traffic Arrival and Time-varying Topology

arXiv: https://arxiv.org/abs/2404.08959 · HTML: https://mlsanity.com/paper/2404.08959/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Apr 2024.

## Built on by (most cited first, 1 of 1)

- [DRL-Based Beam Positioning for LEO Satellite Constellations with Weighted Least Squares](https://mlsanity.com/paper/2511.08852/) (2025)

## Abstract (arXiv)

Low earth orbit (LEO) satellite communication networks have been considered as promising solutions to providing high data rate and seamless coverage, where satellite beam management plays a key role. However, due to the limitation of beam resource, dynamic network topology, beam spectrum reuse, time-varying traffic arrival and service continuity requirement, it is challenging to effectively allocate time-frequency resource of satellite beams to multiple cells. In this paper, aiming at reducing time-averaged beam revisit time and mitigate inter-satellite handover, a beam management problem is formulated for dynamic LEO satellite communication networks, under inter-cell interference and network stability constraints. Particularly, inter-cell interference constraints are further simplified into off-axis angle based constraints, which provide tractable rules for spectrum sharing between two beam cells. To deal with the long-term performance optimization, the primal problem is transformed into a series of single epoch problems by adopting Lyapunov optimization framework. Since the transformed problem is NP-hard, it is further divided into three subproblems, including serving beam allocation, beam service time allocation and serving satellite allocation. With the help of conflict graphs built with off-axis angle based constraints, serving beam allocation and beam service time allocation algorithms are developed to reduce beam revisit time and cell packet queue length. Then, we further develop a satellite-cell service relationship optimization algorithm to better adapt to dynamic network topology. Compared with baselines, numerical results show that our proposal can reduce average beam revisit time by 20.8% and keep strong network stability with similar inter-satellite handover frequency.