A Spatial Resource Allocation Method in Massive MIMO-LEO Satellite Communications

Abstract

massive MIMO technology is critical in the 5G mobile communication system, which can greatly improve the frequency efficiency and communication capacity of terrestrial mobile communication systems, and also provides a new thinking for LEO satellite communication systems to fully reuse frequency between beams. In the paper, according to the massive MIMO-LEO satellite communications theory, we focus on the scenario of demands distributing unevenly spatially, and study the resource allocation problem of LEO satellite communications with full frequency reuse from the spatial perspective. Under the LEO satellite coverage-zoning model, we propose a rasterizing-coverage model for LEO satellites based on the characteristics of massive MIMO, establish a spatial resource allocation model with full frequency reuse, which models the spatial resource allocation problem with the objective of maximizing throughput as an integer programming problem, and put forward a greedy-based spatial resource allocation method. The simulation results show that when the service demand is 100% and the number of spatial resource groups is 16, compared with the fixed-beam method and the hopping-beam allocation method, the resource utilization can be improved respectively by 19% and 26%, and the satisfaction can be improved respectively by 16% and 17.5%, whose improvement are enhanced with the size of the on-board MIMO antenna increasing.