Handover Analysis in Ultra-Dense LEO Satellite Networks With Beamforming Methods

With the ever-growing demands of communication quality and rate, the combination of terrestrial networks and space networks is becoming the next recognized solution. The space-ground integrated network (SGIN) is a massive Internet of Things (IoT) network that accommodates large amounts of mobile terminals. The interactivity of information between those terminals will request higher communication rates and lead to more frequent handovers, which will increase the network burden and degrade the user's experience, especially in ultra-dense Low-Earth Orbit (LEO) satellite networks. In this article, a modified matching algorithm is proposed to get the optimal association matrix between users and base stations. Based on the results, the sum rate of users and the handover rate are calculated. A modified particle swarm optimization (MPSO) method is also proposed to generate the special-shaped beams on the satellites to deal with the complex optimization problems. By combining the MPSO-based beamforming algorithm and the modified matching algorithm, the non-convex sum-rate optimization problem is decomposed into two optimal subproblems, which are solved separately. The simulation results demonstrate that the SGIN significantly outperforms the non-integrated ones in terms of the sum data rate and backhaul capacity. The handover performance under the user mobility model is also discussed.