Satellite constellation design and radio resource management using genetic algorithm

Abstract

Novel strategies for automatic satellite constellation design with satellite diversity and radio resource management are proposed. The automatic satellite constellation design means that some parameters of satellite constellation design can be determined simultaneously. The total number of satellites, the altitude of a satellite, the angle between planes, the angle shift between satellites and the inclination angle are considered in the design. Satellite constellation design is modelled using a multiobjective genetic algorithm. This method is applied to low Earth orbit (LEO), medium Earth orbit (MEO) and hybrid constellations. The use of a genetic algorithm allows automatic satellite constellation design while achieving dual satellite diversity statistics. Furthermore, a strategy for dynamic channel allocation is proposed that uses a genetic algorithm for use in mobile satellite systems (MSS) networks. The main idea behind this algorithm is to use the minimum cost as a metric to provide optimum channel solutions for specified interference constraints. The simulation is designed for a MEO satellite constellation. Using this algorithm, the proposed model outperforms conventional dynamic channel assignment (DCA) schemes in terms of call blocking and call dropping probability. Generally, genetic algorithms are robust to dynamic variations in satellite constellation design and provide resource allocation improvements in DCA in MSS networks.