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Direct Localization for Massive MIMO

机译:大规模MIMO的直接定位

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Large-scale MIMO systems are well known for their advantages in communications, but they also have the potential for providing very accurate localization, thanks to their high angular resolution. A difficult problem arising indoors and outdoors is localizing users over multipath channels. Localization based on angle of arrival (AOA) generally involves a two-step procedure, where signals are first processed to obtain a user's AOA at different base stations, followed by triangulation to determine the user's position. In the presence of multipath, the performance of these methods is greatly degraded due to the inability to correctly detect and/or estimate the AOA of the line-of-sight (LOS) paths. To counter the limitations of this two-step procedure which is inherently suboptimal, we propose a direct localization approach in which the position of a user is localized by jointly processing the observations obtained at distributed massive MIMO base stations. Our approach is based on a novel compressed sensing framework that exploits channel properties to distinguish LOS from non-LOS signal paths, and leads to improved performance results compared to previous existing methods.
机译:大型MIMO系统以其在通讯方面的优势而闻名,但由于其高角度分辨率,它们还具有提供非常精确的定位的潜力。室内和室外出现的一个难题是将用户定位在多径通道上。基于到达角(AOA)的定位通常涉及两步过程,首先处理信号以获得不同基站的用户AOA,然后进行三角测量以确定用户的位置。在存在多路径的情况下,由于无法正确检测和/或估计视线(LOS)路径的AOA,因此这些方法的性能会大大降低。为了克服这种固有地次优的两步过程的局限性,我们提出了一种直接定位方法,其中通过联合处理在分布式大规模MIMO基站获得的观测值来定位用户的位置。我们的方法基于一种新颖的压缩传感框架,该框架利用信道属性将LOS与非LOS信号路径区分开,并且与以前的现有方法相比,可以提高性能。

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