面向低轨巨型星座的多目标卫星接入优化

低轨巨型星座可以提供全球无缝覆盖的卫星通信服务，但也会导致用户被卫星多重覆盖，如何选择最优的卫星进行接入，成为低轨巨型星座接入技术的关键问题。对此，提出一种基于粒子群的多目标卫星接入优化算法。综合考虑星地距离、卫星剩余可服务时间和卫星剩余负载等目标函数，根据不同业务类型的QoS需求，对参数赋予相应的权值；针对可视卫星数量多且动态变化的特点，通过粒子群算法进行低复杂度求解。仿真表明，相较于对比算法，所提算法对星地距离和卫星剩余可服务时间进行了优化折中，保障了服务时间和通信质量，提高了接入成功率，能够灵活满足用户的不同业务类型需求，适应用户业务不同时空分布以及业务离散化的场景。

Multi-objective satellite access optimization for Low Earth Orbit mega-constellations

Low Eatht Orbit mega-constellations can provide global seamless coverage of satellite communication services, but also lead to users being covered by multiple satellites. How to choose the optimal satellite for access has become a key issue in the access technology of low-orbit mega-constellations. In response to the above problems, this paper proposes a multi-objective satellite access optimization algorithm based on particle swarm, the objective function comprehensively considers the distance between the satellite and the earth, the remaining service time of the satellite, and the remaining load of the satellite. According to the Quality of Service(QoS) requirements of different traffic types, corresponding weights are assigned to the parameters. Finally, considering the characteristics of a large number of visible satellites and dynamic changes, a low-complexity solution is obtained through the particle swarm algorithm. Simulations show that compared with the comparison algorithm, the proposed algorithm optimizes the trade-off between the distance from the satellite to the earth and the remaining service time of the satellite, guarantees the service time and communication quality, improves the success rate of access, and can flexibly meet the needs of users'' different traffic types, adapt to the scenario of users'' traffic distribution at different time and spaces, and the scenario of traffic discretization.