Abstract
A novel strategy for automatic satellite constellation design with satellite diversity is proposed. The automatic satellite constellation design means some parameters of satellite constellation design can be determined simultaneously. The total number of satellites, the altitude of satellite, the angle between planes, the angle shift between satellites and the inclination angle are considered for automatic satellite constellation design. Satellite constellation design is modelled using a multiobjective genetic algorithm. This method is applied to LEO, MEO and hybrid constellations. The advantage of this algorithm is automatic satellite constellation design whilst achieving dual satellite diversity statistics. Furthermore a new strategy of dynamic channel allocation is proposed using a genetic algorithm for use in MSS networks. The main idea behind this algorithm is to use minimum cost as a metric to provide optimum channel solutions for specified interference constraints. The frequency reuse condition for all spotbeams is investigated as a function of time. The update interval time and the sampling time are introduced in order to track time valiant coefficients and constraints of the algorithm. The method is demonstrated for S-UMTS based on a MEO satellite constellation. Using this algorithm, it is shown that the proposed model outperforms conventional DCA schemes in terms of capacity of the system and Quality of Service (QoS).We show in the thesis that the genetic algorithm is a robust method for calculation of dynamic variations in satellite constellation design and provides resource allocation improvements over DCA in MSS system networks.