地球多波束卫星匹配需求的推动者:动态波束形成,预编码,还是两者兼而有之?

H. Chaker, N. Maturo, S. Chatzinotas, H. Chougrani, W. Martins, J. Grotz
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引用次数: 4

摘要

在趋势卫星通信应用中,通信量需求不仅是快速增长的,而且是时空变化的。这促使部署具有灵活无线电资源管理和传输技术的高通量卫星系统。与目前用于GEO有效载荷的常规波束布局计划(RBLP)相比,未来的灵活有效载荷能够使用动态波束形成(DBF),以便使用高度指向性和交通自适应波束模式照亮覆盖区域。与RBLP相比,自适应波束布局(ABLP)中的波束模式可能具有不规则形状和相互重叠,可能导致过多的波束间干扰(IBI)。在这项工作中,我们评估了DBF和预编码的组合,因为后者承诺在限制干扰的条件下具有高吞吐量,并得到最近的DVB-S2X规范的支持。在现实的非均匀流量模式下,我们比较了典型RBLP和ABLP在有预编码和没有预编码时的流量匹配性能。通过比较,我们发现DBF能够使用均匀平衡光束间需求分布的ABLP显著减少容量不匹配。注意到ABLP是IBI不可知的,因此建立了一个不可预测的干扰环境。在这种情况下,预编码能够通过全频率重用可靠地提供高吞吐量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Enablers for matching demand in geo multi-beam satellites: dynamic beamforming, precoding, or both?
In trending satellite communication applications, the traffic demand is not only rapidly increasing, it is also spatiotemporally evolving. This motivates the deployment of high throughput satellite systems with flexible radio resource management and transmission techniques. In contrast to regular beam layout plans (RBLP) currently used in GEO payloads, future flexible payloads are capable of dynamic beamforming (DBF) in order to illuminate the coverage area using highly-directive and traffic-adaptive beampatterns. The beampatterns in an adaptive beam layout plan (ABLP) can have irregular shapes and mutual overlaps, potentially causing excessive inter-beam interferences (IBI) compared to the RBLP case. In this work, we evaluate the combination of DBF and precoding as the latter promises high throughputs in interference-limited conditions and is supported by the recent DVB-S2X norm. Under realistic non-uniform traffic patterns, we compare a typical RBLP against an ABLP in terms of their traffic matching performances with and without precoding. Through the comparisons, we show that DBF enables to significantly reduce the capacity mismatches using an ABLP that uniformly balances the demand distribution across beams. Noting that the ABLP is IBI agnostic, an unpredictable interference environment is built. In such conditions, precoding enables to reliably provide high throughputs through full frequency reuse.
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