Research into a least multipath based wireless local positioning technique for massive MIMO systems in extreme multipath conditions

极端多径条件下大规模MIMO系统基于最少多径的无线本地定位技术研究

• 批准号: 468715998
• 负责人: Professor Dr.-Ing. Martin Vossiek
• 金额: --
• 依托单位: Lehrstuhl für Hochfrequenztechnik
• 依托单位国家: 德国
• 项目类别: Research Grants
• 资助国家: 德国
• 项目状态: 未结题
• 来源: https://gepris.dfg.de/gepris/projekt/468715998?language=en
• 关键词: Research; into; least; multipath; based

In future wireless communication networks (5G, 6G, etc.), massive MIMO systems increase the achievable data rate. Since the achievable data rate depends on the independence of the spatially recorded information (spatial diversity), large antenna arrays are favorable. In this project, the spatial diversity of Massive MIMO systems is used to enable exact indoor localization even under extreme multipath conditions. While UWB systems attempt to isolate the direct path from the multipath propagation by increasing the bandwidth, the impulse responses of the line of sight (LOS) and the multipath propagation overlap in localization systems with limited bandwidth. Therefore, a LOS identification, which is solely based on the evaluation of a single path, is not possible. Hence, in this project the spatial diversity of Massive MIMO systems is used to separate the common LOS of all receive paths from the superimposed multipath propagation, which decorrelates with increasing antenna distance. For this purpose, a least multipath metric is developed to replace the commonly established least squares metric. Here, the aim is to estimate the multipath propagation, remove it from the signal, and thereby, drastically improve the localization accuracy. For this purpose, the receive channel of each antenna is superimposed by an individual hypothetical multipath channel during the measurement evaluation. While the LOS path at each receiver directly depends on the transmitter’s position, the multipath propagation towards all receivers differ and are sparse, because they are caused by few reflections at the environment. Hence, at the correct transmitter position, the remaining receive signal can be described with only little further multipath propagation, whereas at an incorrectly assumed transmitter position, the LOS path has to be described using additional multipath propagation. According to the compressed sensing theory, the multipath propagation can then be estimated with a small L1 norm at the correct transmitter position. Hence, the least multipath position estimation is performed by a simultaneous minimum search of both the transmitter position and the corresponding multipath propagation. Since the evaluation of the receive channels’ relative phase information is increasing the resolution of the transmitter position, the LOS paths can now be separated from the multipath propagation. Vice versa, the effect of the multipath propagation is simultaneously subtracted from the evaluated phases and hence, the localization accuracy increases. Equally important to the novel localization concept, an equivalent calibration concept will be investigated. For this purpose, again the proposed least multipath metric will be used. The novel calibration and localization concept will be validated by measurements using a unique massive MIMO array, which is already available at the LHFT.

在未来的无线通信网络（5G、6G 等）中，大规模 MIMO 系统提高了可实现的数据速率，因为可实现的数据速率取决于空间记录信息的独立性（空间分集），因此大型天线阵列是有利的。项目中，大规模 MIMO 系统的空间分集用于即使在极端多径条件下也能实现精确的室内定位，而 UWB 系统试图通过增加带宽、脉冲响应来将直接路径与多径传播隔离。视线（LOS）和多径传播在带宽有限的定位系统中重叠，因此，仅基于单个路径的评估的LOS识别是不可能的。因此，在该项目中，大规模的空间分集。 MIMO 系统用于将所有接收路径的公共 LOS 与叠加的多径传播分开，这与增加的天线距离无关。为此，开发了最小多径度量来取代通常建立的最小二乘度量。是估计多径传播，将其从信号中去除，从而显着提高定位精度。为此，在测量评估期间，每个天线的接收信道都由单独的假设多径信道叠加。每个接收器直接取决于发射器的位置，向所有接收器的多径传播不同且稀疏，因为它们是由环境中的少量反射引起的，因此，在正确的发射器位置，剩余的接收信号可以用只需要很少的进一步多径传播，而在错误假设的发射机位置处，必须使用额外的多径传播来描述LOS路径，然后可以在正确的发射机位置处使用小的L1范数来估计多径传播。因此，通过同时最小搜索发射机位置和相应的多径传播来执行最小多径位置估计，因为接收通道的相对相位信息的评估提高了发射机位置的分辨率。现在可以将 LOS 路径与多径传播分开，反之亦然，同时从评估的相位中减去多径传播的影响，因此，与新颖的定位概念同样重要的是，将研究等效的校准概念。为此，将再次使用所提出的最少多径度量，并通过使用 LHFT 已提供的独特大规模 MIMO 阵列进行测量来验证。