论文标题
多光束卫星通信系统的流量模拟器
Traffic Simulator for Multibeam Satellite Communication Systems
论文作者
论文摘要
假设从头开始设计了多层卫星通信系统,以最大程度地利用资源利用,以满足预期的交通需求。这里的主要设计挑战是设置最佳系统参数,例如服务梁的数量,梁方向和尺寸以及传输功率。本文旨在开发一种工具,即多光束卫星交通模拟器,有助于解决这些基本挑战,更重要的是,为大规模环境中卫星网络的时空交通模式提供了理解。具体而言,通过处理可信数据集的流量分配包括三个主要输入信息类别:(i)宽带固定卫星服务(FSS),(ii)航空卫星通信的种群分布以及(iii)海上服务的船只分布。此交通模拟器除了时间,终端的位置和交通需求外,还将这些三维信息结合在一起。此外,在这项工作中已经考虑了逼真的卫星光束图案,因此,已经提出了一种算法来界定每个卫星束的覆盖范围边界,然后计算每个梁的足迹处的异构交通需求。此外,已经开发了另一种算法来捕获卫星通道的固有属性和多光束干扰的效果。如今,卫星流量的数据驱动建模对于设计创新的通信系统,例如预编码和梁跳跃以及设计有效的资源管理算法至关重要。
Assume that a multibeam satellite communication system is designed from scratch to serve a particular area with maximal resource utilization and to satisfactorily accommodate the expected traffic demand. The main design challenge here is setting optimal system parameters such as number of serving beams, beam directions and sizes, and transmit power. This paper aims at developing a tool, multibeam satellite traffic simulator, that helps addressing these fundamental challenges, and more importantly, provides an understanding to the spatial-temporal traffic pattern of satellite networks in large-scale environments. Specifically, traffic demand distribution is investigated by processing credible datasets included three major input categories of information: (i) population distribution for broadband Fixed Satellite Services (FSS), (ii) aeronautical satellite communications, and (iii) vessel distribution for maritime services. This traffic simulator combines this three-dimensional information in addition to time, locations of terminals, and traffic demand. Moreover, realistic satellite beam patterns have been considered in this work, and thus, an algorithm has been proposed to delimit the coverage boundaries of each satellite beam, and then compute the heterogeneous traffic demand at the footprint of each beam. Furthermore, another algorithm has been developed to capture the inherent attributes of satellite channels and the effects of multibeam interference. Data-driven modeling for satellite traffic is crucial nowadays to design innovative communication systems, e.g., precoding and beam hopping, and to devise efficient resource management algorithms.