(超)5G网络中流量驱动的探测参考信号资源分配

Claudio Fiandrino, Giulia Attanasio, M. Fiore, J. Widmer
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引用次数: 5

摘要

超越5G的移动网络必须支持广泛的性能要求和前所未有的灵活性。为此,通过增加天线单元的数量,大规模MIMO是提高频谱效率从而扩大网络容量的关键技术。这也增加了信道状态信息估计的开销,获得准确的信道状态信息是大规模MIMO系统中的一个基本问题。在本文中,我们的重点是调度上行探测参考信号(SRSs)携带导频符号用于CSI估计。在5G以后系统的大量用户和高负载下,SRSs可用的资源数量有限,使得传统的3GPP定期分配方案效率低下。我们设计了TRADER,一个SRS资源分配框架,通过利用基于机器学习的基站级短期流量预测,最大限度地减少信道估计的年龄。通过对突发流量的预测,TRADER调度SRS资源,在流量到达之前获得每个用户的CSI。广泛的真实移动网络跟踪实验表明,我们的解决方案在高负载情况下是高效和稳健的:相对于非周期性SRS的轮循调度,TRADER在相干时间内提供更频繁的CSI(给定情况下高达5倍),导致信道增益高达2db。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Traffic-Driven Sounding Reference Signal Resource Allocation in (Beyond) 5G Networks
Beyond 5G mobile networks have to support a wide range of performance requirements and unprecedented levels of flexibility. To this end, massive MIMO is a critical technology to improve spectral efficiency and thus scale up network capacity, by increasing the number of antenna elements. This also increases the overhead of Channel State Information (CSI) estimation and obtaining accurate CSI is a fundamental problem in massive MIMO systems. In this paper, we focus on scheduling uplink Sounding Reference Signals (SRSs) that carry pilot symbols for CSI estimation. Under the large number of users and high load that are expected to characterize beyond 5G systems, the limited amount of resources available for SRSs makes the legacy 3GPP periodic allocation scheme largely inefficient. We design TRADER, an SRS resource allocation framework that minimizes the age of channel estimates by taking advantage of machine learning-based short-term traffic forecasts at the base station level. By anticipating traffic bursts, TRADER schedules SRS resources so as to obtain CSI for each user right before the corresponding traffic arrives. Experiments with extensive real-world mobile network traces show that our solution is efficient and robust in high load scenarios: with respect to a round robin schedule of aperiodic SRS, TRADER provides more often CSI within the coherence time (up to 5× for given scenarios), leading to channel gains of up to 2 dB.
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