# Joint Beam Placement and Load Balancing Optimization for Non-Geostationary Satellite Systems

arXiv: https://arxiv.org/abs/2207.14633 · HTML: https://mlsanity.com/paper/2207.14633/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Jul 2022.

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

- [Multi Agent Reinforcement Learning for Sequential Satellite Assignment Problems](https://mlsanity.com/paper/2412.15573/) (2024)

## Abstract (arXiv)

Non-geostationary (Non-GSO) satellite constellations have emerged as a promising solution to enable ubiquitous high-speed low-latency broadband services by generating multiple spot-beams placed on the ground according to the user locations. However, there is an inherent trade-off between the number of active beams and the complexity of generating a large number of beams. This paper formulates and solves a joint beam placement and load balancing problem to carefully optimize the satellite beam and enhance the link budgets with a minimal number of active beams. We propose a two-stage algorithm design to overcome the combinatorial structure of the considered optimization problem providing a solution in polynomial time. The first stage minimizes the number of active beams, while the second stage performs a load balancing to distribute users in the coverage area of the active beams. Numerical results confirm the benefits of the proposed methodology both in carrier-to-noise ratio and multiplexed users per beam over other benchmarks.