论文标题
Fronthaul受约束的分布式MIMO C-RAN的基于MF的尺寸降低信号压缩
MF-based Dimension Reduction Signal Compression for Fronthaul-Constrained Distributed MIMO C-RAN
论文作者
论文摘要
在这项工作中，我们提出了一种带有多Antenna接收器的分布式MIMO系统的Fronthaul压缩方案，其中，在信号定量之前，通过将接收信号的过滤带有本地用户通道矢量的子集匹配，在每个接收方进行尺寸降低。通过基于全局通道信息选择这些匹配的滤波器向量，可以通过少量信号组件捕获高比例的潜在容量，然后可以使用局部信号压缩有效地压缩它们。我们概述了一种贪婪算法，用于为每个接收器选择匹配的过滤向量，以及用于量化它们的本地变换编码方法，为所得系统总和和用户能力提供表达。然后，我们证明该方案很容易修改以说明接收器的CSI不完美。数值结果表明，在较低的信号维度下，该方案能够非常接近Fronthaul限制式的切割集界限，并在所有操作点上，尤其是在高SNR处表现出速率容量折衷与局部压缩的显着改善。
In this work we propose a fronthaul compression scheme for distributed MIMO systems with multi-antenna receivers, in which, prior to signal quantisation, dimension reduction is performed at each receiver by matched filtering the received signal with a subset of the local user channel vectors. By choosing these matched filter vectors based on global channel information, a high proportion of the potential capacity may be captured by a small number of signal components, which can then be compressed efficiently using local signal compression. We outline a greedy algorithm for selecting the matched filtering vectors for each receiver, and a local transform coding approach for quantising them, giving expressions for the resulting system sum and user capacities. We then show that the scheme is easily modified to account for imperfect CSI at the receivers. Numerical results show that with a low signal dimension the scheme is able to operate very close to the cut-set bound in the fronthaul-limited regime, and demonstrates significant improvements in rate-capacity trade-off versus local compression at all operating points, particularly at high SNR.
