Multi-layer satellite network resource management based on genetic algorithm

The air-space-ground integrated network architecture is one of the core directions of 6G. Its network architecture is based on the ground cellular mobile network, combined with the characteristics of wide coverage, flexible deployment, and efficient broadcasting of broadband satellite communications, and through the deep integration of a variety of heterogeneous networks to achieve the full coverage of sea, land and air, which will bring new opportunities for the marine, airborne, transnational, space and ground applications. However, the satellite network is a highly complex heterogeneous multi-layer system, how to realize the capacity management among multi-layer satellites is still a challenging. In this paper, we first investigate the problem of capacity management in the three-layer heterogeneous satellite network, using Quality of Experience (QoE) as the optimization target for resource allocation. Then, we built a complex network model architecture of mobile users, base stations, low-orbit satellites, and high-orbit satellites. Based on the genetic algorithm to optimize capacity allocation, we evaluate and compare the proposed algorithm with traditional optimization algorithms in terms of performance and algorithm complexity.