An Improved Beam Switching Genetic Algorithm for LEO Multi-Beam Satellite Constellation

In order to reduce inter-beam interference and resource wastage caused by beam overlap of low earth orbit (LEO) multi-beam satellite constellation, an improved beam switching genetic algorithm (BSGA) is proposed. Firstly, by analyzing the Iridium constellation multi-beam system, a global digital model of the constellation, multi-beam, overlapping coverage, and beam switching optimization problem is established sequentially. To improve the practical engineering usability of the algorithm, the actual pattern is used instead of the traditional spot beam for coverage analysis. Then, a genetic algorithm with optimization control strategy is proposed, to efficiently solve the beam switching problem (BSP). By analyzing the law of beam overlap after constellation networking to control the optimization direction, the convergence of the BSGA is accelerated. Simulation results show that the proposed BSGA can effectively minimize the inter-beam interference and resource wastage of LEO multi-beam satellite constellation. This phenomenon shows that the proposed BSGA can be widely used in the dynamic management of large-scale LEO satellite networking communication.