论文标题
矢量量化方法，用于无细胞大型MIMO系统中的访问点位置
Vector Quantization Methods for Access Point Placement in Cell-Free Massive MIMO Systems
论文作者
论文摘要
我们在最佳吞吐量的背景下检查了无上行链路无单元的接入点（AP）放置问题。在这方面，我们提出了两个主要位置问题，即总和利率和最低利率最大化问题，并讨论与一些简单场景的帮助解决基本优化问题相关的挑战。作为对AP放置问题的实际解决方案，我们建议一种矢量量化（VQ）方法。通过检查三种基于VQ的解决方案，研究了VQ方法对无细胞AP放置的适用性。首先，描述了标准VQ方法，即Lloyd算法（使用平方错误失真函数）。其次，应用了对分布空间进行连续分区的树结构化VQ（TSVQ）。第三，概述了概率密度函数优化的VQ（PDFVQ）过程，从而实现有效的，低的复杂性和可扩展的位置，并针对大量分布式分布式多输入 - 信息输出（MIMO）方案。尽管基于VQ的解决方案不能明确解决无单元的AP放置问题，但数值实验表明它们的总和和最低速率性能足够好，并为基于梯度的优化方法提供了一个很好的起点。在VQ解决方案中，PDFVQ与其他VQ方法具有优势，在总和和最低利率之间提供了良好的权衡。
We examine the problem of uplink cell-free access point (AP) placement in the context of optimal throughput. In this regard, we formulate two main placement problems, namely the sum rate and minimum rate maximization problems, and discuss the challenges associated with solving the underlying optimization problem with the help of some simple scenarios. As a practical solution to the AP placement problem, we suggest a vector quantization (VQ) approach. The suitability of the VQ approach to cell-free AP placement is investigated by examining three VQ-based solutions. First, the standard VQ approach, that is the Lloyd algorithm (using the squared error distortion function) is described. Second, the tree-structured VQ (TSVQ), which performs successive partitioning of the distribution space is applied. Third, a probability density function optimized VQ (PDFVQ) procedure is outlined, which enables efficient, low complexity, and scalable placement, and is aimed at a massive distributed multiple-input-multiple-output (MIMO) scenario. While the VQ-based solutions do not solve the cell-free AP placement problems explicitly, numerical experiments show that their sum and minimum rate performances are good enough, and offer a good starting point for gradient-based optimization methods. Among the VQ solutions, PDFVQ, with advantages over the other VQ methods, offers a good trade-off between sum and minimum rates.
