多波束卫星系统中多播预编码的地理调度

A. Guidotti, A. Vanelli-Coralli
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引用次数: 30

摘要

目前最先进的高通量卫星系统通过多波束架构提供广域连接。由于下一代卫星通信(SatCom)期望实现的巨大系统吞吐量要求,传统的四色频率重用方案已经不够了,并且正在考虑多波束卫星通信的全频率重用等更积极的解决方案。这些方法需要先进的干扰管理技术来应对发送端(如预编码)和接收端(如多用户检测(MUD))显著增加的波束间干扰。对于前者,在为卫星通信系统设计时出现了一些特殊的挑战。特别是,多个用户在同一发送无线电帧中复用,因此在计算预编码系数时需要考虑多个信道矩阵。在以前的工作中,主要关注用户的聚类和预编码设计。然而,即使实现了显著的吞吐量增益,也没有对系统调度算法对多播预编码的影响进行分析,通常假定多播预编码是随机的。在本文中,我们通过表明,尽管整体系统性能得到了改善,但随机调度程序并不能正确处理预编码算法性能不佳的特定场景,从而关注这方面。基于这些考虑,我们设计了一种地理调度算法(GSA),旨在提高这些关键场景下的预编码性能,从而提高系统级的性能。通过大量的数值模拟,我们表明,相对于传统的随机调度,提出的GSA提供了显著的性能改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Geographical Scheduling for Multicast Precoding in Multi-Beam Satellite Systems
Current State-of-the-Art High Throughput Satellite systems provide wide-area connectivity through multi-beam architectures. Due to the tremendous system throughput requirements that next generation Satellite Communications (SatCom) expect to achieve, traditional 4-colour frequency reuse schemes are not sufficient anymore and more aggressive solutions as full frequency reuse are being considered for multi-beam SatCom. These approaches require advanced interference management techniques to cope with the significantly increased inter-beam interference both at the transmitter, e.g., precoding, and at the receiver, e.g., Multi User Detection (MUD). With respect to the former, several peculiar challenges arise when designed for SatCom systems. In particular, multiple users are multiplexed in the same transmission radio frame, thus imposing to consider multiple channel matrices when computing the precoding coefficients. In previous works, the main focus has been on the users’ clustering and precoding design. However, even though achieving significant throughput gains, no analysis has been performed on the impact of the system scheduling algorithm on multicast precoding, which is typically assumed random. In this paper, we focus on this aspect by showing that, although the overall system performance is improved, a random scheduler does not properly tackle specific scenarios in which the precoding algorithm can poorly perform. Based on these considerations, we design a Geographical Scheduling Algorithm (GSA) aimed at improving the precoding performance in these critical scenarios and, consequently, the performance at system level as well. Through extensive numerical simulations, we show that the proposed GSA provides a significant performance improvement with respect to the legacy random scheduling.
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