Fast Beam Placement for Ultra-Dense LEO Networks

TL;DR

This paper introduces fast algorithms for optimal beam placement in ultra-dense LEO satellite networks, improving link quality and resource efficiency with reduced computation time.

Contribution

It proposes two novel algorithms based on modified K-means and graph theory for rapid beam placement in dense LEO satellite systems, addressing a key resource allocation challenge.

Findings

Algorithms outperform benchmarks in channel gain-to-noise ratio

Significant reduction in computation time achieved

Effective load balancing among beams demonstrated

Abstract

Low Earth orbit (LEO) satellites has brought about significant improvements in wireless communications, characterized by low latency and reduced transmission loss compared to geostationary orbit (GSO) satellites. Ultra-dense LEO satellites can serve many users by generating active beams effective to their locations. The beam placement problem is challenging but important for efficiently allocating resources with a large number of users. This paper formulates and solves a fast beam placement optimization problem for ultra-dense satellite systems to enhance the link budget with a minimum number of active beams (NABs). To achieve this goal and balance load among beams within polynomial time, we propose two algorithms for large user groups exploiting the modified K-means clustering and the graph theory. Numerical results illustrate the effectiveness of the proposals in terms of the statistical channel gain-to-noise ratio and computation time over state-of-the-art benchmarks.