上海科技大学知识管理系统

LEO constellation network has become a promising approach

for global communications, due to its global coverage, lower latency, and

flexible construction. However, because of the limited coverage of a single

satellite and the high-speed space-ground relative movement, how

to leverage the precise satellite resources to satisfy the user terminals’

requests is an important issue. Beam hopping technique is an efficient

way to handle this issue by scheduling the onboard resource according

to the distribution of terminals’ requests. In this paper we propose a

cooperative beam hopping for LEO constellation network, where multiple

satellites provide service for the user terminals in the multi-coverage

areas. The problem is innovatively modeled as a LASSO problem considering

its sparsity, and machine learning methods are introduced to

optimize it. Compared with the fixed beam system, our proposed scheme

achieves better performance in terms of resource utilization and average

user satisfaction rate.