Low earth orbit (LEO) satellite communications can provide ubiquitous and reliable services, making it an essential part of the Internet of Everything network. Beam hopping (BH) is an emerging technology for effectively addressing the issue of low resource utilization caused by the non-uniform spatio-temporal distribution of traffic demands. However, how to allocate multi-dimensional resources in a timely and efficient way for the highly dynamic LEO satellite systems remains a challenge. This paper proposes a joint beam scheduling and power optimization beam hopping (JBSPO-BH) algorithm considering the differences in the geographic distribution of sink nodes. The JBSPO-BH algorithm decouples the original problem into two sub-problems. The beam scheduling problem is modelled as a potential game, and the Nash equilibrium (NE) point is obtained as the beam scheduling strategy. Moreover, the penalty function interior point method is applied to optimize the power allocation. Simulation results show that the JBSPO-BH algorithm has low time complexity and fast convergence and achieves better performance both in throughput and fairness. Compared with greedy-based BH, greedy-based BH with the power optimization, round-robin BH, Max-SINR BH and satellite resource allocation algorithm, the throughput of the proposed algorithm is improved by 44.99%, 20.79%, 156.06%, 15.39% and 8.17%, respectively.

翻译：低地球轨道卫星通信能够提供无处不在且可靠的服务，使其成为万物互联网络的重要组成部分。跳波束技术是有效解决因业务需求时空分布不均导致的资源利用率低问题的关键技术。然而，如何针对高度动态的低轨卫星系统及时且高效地分配多维资源仍然是一个挑战。本文提出了一种考虑汇聚节点地理分布差异的联合波束调度与功率优化跳波束算法。该算法将原始问题解耦为两个子问题：波束调度问题被建模为势博弈，并获取纳什均衡点作为波束调度策略；同时，采用罚函数内点法对功率分配进行优化。仿真结果表明，所提算法具有低时间复杂度和快速收敛特性，并在吞吐量和公平性方面均实现了更优性能。与基于贪婪的跳波束算法、基于贪婪且带功率优化的跳波束算法、轮询跳波束算法、最大信干噪比跳波束算法及卫星资源分配算法相比，所提算法的吞吐量分别提升了44.99%、20.79%、156.06%、15.39%和8.17%。