For extensive coverage areas, multi-beam high throughput satellite (MB-HTS) communication is a promising technology that plays a crucial role in delivering broadband services to many users with diverse Quality of Service (QoS) requirements. This paper focuses on MB-HTS systems where all beams reuse the same spectrum. In particular, we propose a novel user scheduling and power allocation design capable of providing guarantees in terms of the individual QoS requirements while maximizing the system throughput under a limited power budget. Precoding is employed in the forward link to mitigate mutual interference at the users in multiple-access scenarios over different coherence time intervals. The combinatorial optimization structure from user scheduling requires an extremely high cost to obtain the global optimum even when a reduced number of users fit into a time slot. Therefore, we propose a heuristic algorithm yielding good trade-off between performance and computational complexity, applicable to a static operation framework of geostationary (GEO) satellite networks. Although the power allocation optimization is signomial programming, non-convex on a standard form, the solution can be lower bounded by the global optimum of a geometric program with a hidden convex structure. A local solution to the joint user scheduling and power allocation problem is consequently obtained by a successive optimization approach. Numerical results demonstrate the effectiveness of our algorithms on large-scale systems by providing better QoS satisfaction combined with outstanding overall system throughput.
翻译:对于广泛的覆盖地区,多波束高载量卫星(MB-HTS)通信是一种大有希望的技术,在向许多用户提供宽带服务方面发挥着关键作用,这些用户的服务质量要求各不相同。本文件侧重于所有光束都可再利用相同频谱的MB-HTS系统。特别是,我们建议采用新的用户时间安排和电力分配设计,在有限的电力预算下,在最大程度实现系统吞吐量的同时,为保证单个的QOS要求提供保障。预先编码用于前端链接,以减少用户在不同的时间间隔内在多重接入情景下相互干扰。用户排期的组合优化结构需要极高的成本才能获得全球最佳的宽带服务,即使用户数量减少,能够重新利用相同的频谱频谱频谱。因此,我们提议一种超常的算法,在性能和计算复杂性之间实现良好的交易,适用于静止卫星网络的静态操作框架。尽管电力分配是象征性的,标准格式上的非电流,但解决方案可以受到全球最佳组合的系统约束程度较低。通过隐藏的用户系统优化配置,通过连续的系统优化的系统安排,从而展示一个隐藏的用户优化的系统对结果的进度安排,从而展示一个更好的系统对结果的系统进行更好的配置。