MU-MIMO网络中的自适应视频流
Adaptive Video Streaming in MU-MIMO Networks
摘要：
我们认为扩展和改进我们以前的工作动态自适应视频流在多小区多用户“小小区”的无线网络。以前，我们处理的情况下，单天线基站，从网络效用最大化（NUM）制定，我们设计了一个“推”调度策略，其中用户将请求顺序视频块可能不同的基站与自适应视频质量，和基站调度他们的下行链路传输，以稳定他们的传输队列。在本文中，我们考虑一个“拉”的策略，每个用户维护一个请求队列，这样用户就可以跟踪有效交付的视频块。拉取方案允许按回放顺序下载块，而不会跳过或错过它们。另外，受小型小区网络中的最近/即将到来的进展（例如，在最近的IEEE802.11ac标准的波-2中），我们将我们的动态流方法扩展到能够进行多用户MIMO下行链路的基站的情况，即，通过空间复用在同一时频隙上为多个用户提供服务。通过利用高维MIMO信道的“信道硬化”效应，我们设计了一个低复杂度的用户选择方案来解决底层的最大加权速率调度，它可以很容易地实现，并在每个基站独立运行。通过模拟，我们展示了MIMO在视频流QoE指标方面的增益，如预缓冲和重新缓冲时间。
英文摘要：
We consider extensions and improvements on our previous work on dynamic adaptive video streaming in a multi-cell multiuser ``small cell'' wireless network. Previously, we treated the case of single-antenna base stations and, starting from a network utility maximization (NUM) formulation, we devised a ``push'' scheduling policy, where users place requests to sequential video chunks to possibly different base stations with adaptive video quality, and base stations schedule their downlink transmissions in order to stabilize their transmission queues. In this paper we consider a ``pull'' strategy, where every user maintains a request queue, such that users keep track of the video chunks that are effectively delivered. The pull scheme allows to download the chunks in the playback order without skipping or missing them. In addition, motivated by the recent/forthcoming progress in small cell networks (e.g., in wave-2 of the recent IEEE 802.11ac standard), we extend our dynamic streaming approach to the case of base stations capable of multiuser MIMO downlink, i.e., serving multiple users on the same time-frequency slot by spatial multiplexing. By exploiting the ``channel hardening'' effect of high dimensional MIMO channels, we devise a low complexity user selection scheme to solve the underlying max-weighted rate scheduling, which can be easily implemented and runs independently at each base station. Through simulations, we show MIMO gains in terms of video streaming QoE metrics like the pre-buffering and re-buffering times.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
