SpecEES: Collaborative Research: Stochastic Geometry Meets Channel Measurements: Comprehensive Modeling, Analysis,Fundamental Design-tradeoffs in Real-world Massive-MIMO Networks

SpecEES：协作研究：随机几何满足信道测量：现实世界大规模 MIMO 网络中的综合建模、分析、基本设计权衡

• 批准号: 1731694
• 负责人: Andreas Molisch
• 金额: $ 34.57万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-01 至 2022-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1731694&HistoricalAwards=false
• 关键词: SpecEES; Collaborative; Research; Stochastic; Geometry

One promising solution to handle the ever-increasing demand for wireless capacity is to deploy significantly higher number of antenna elements at the base station compared to the number of users in the cell. This so called Massive MIMO approach creates extra degrees of freedom that can be used to "shape" beams, thus enhancing both the energy and spectral efficiency of communication links. Massive MIMO can be implemented in a variety of ways. One extreme is the concentrated implementation in which hundreds of antennas are deployed at a single location within a cell. On the other extreme is the fully distributed implementation in which hundreds of single-antenna remote radio heads, distributed throughout the cell, are connected to a common baseband processing unit, thus forming a distributed base station. In between these extremes is the relatively less-investigated case of semi-distributed implementation in which multi-antenna remote radio heads are distributed across the cell. While the massive MIMO idea has been around for several years now, our understanding of the performance of these systems is still limited. This is mainly due to the lack of real-world propagation models (especially for the semi-distributed implementations) as well as mathematical tools that can expose performance trends for different spatial distributions of the users and base stations, both of which are known to significantly impact the performance of these systems. The main goal of this research is to develop a transformative measurements-driven analytical approach to enable the efficient deployment of massive MIMO networks ultimately leading to better customer experience, via improved spectral efficiency, and greener wireless communications, via improved energy efficiency. All the key outcomes of this project will be widely disseminated through publications, tutorials, and industry collaborations. The proposed research will develop a comprehensive measurement-driven approach to the spectral and energy efficiency analyses of massive MIMO systems by blending ideas from multiple disciplines, such as communication theory, stochastic geometry, point process theory, and propagation modeling, yielding the following key innovations: (1) stochastic geometry-aware spectral and energy efficiency metrics to facilitate fundamental analysis and fair comparison across different flavors of massive MIMO, (2) new stochastic geometry approaches to the coverage analysis of concentrated, distributed, and semi-distributed massive MIMO systems, (3) new results on the channel characterization for distributed massive MIMO systems under different classes of propagation models, (4) extensive measurement campaign (tailored to massive MIMO systems) using a one-of-its-kind channel sounder, (5) fundamentally new channel models for semi-deterministic massive MIMO setups that will incorporate correlation of the pathloss and dispersion metrics, in addition to traditionally modeled correlation of the shadowing from user to different RRHs, and (6) new massive-MIMO channel models for the millimeter-wave frequencies. This project will thus combine the powerful spatial modeling tools from stochastic geometry with real-world massive MIMO channel models to compare and contrast the performance of different flavors of massive MIMO under real-world operational constraints, which will directly impact the design, operation, and management of future cellular networks.

处理对无线容量的不断增长的需求的一个有希望的解决方案是在基站处部署与小区中的用户数量相比显著更高数量的天线元件。这种所谓的大规模MIMO方法创造了额外的自由度，可用于“成形”波束，从而提高通信链路的能量和频谱效率。大规模MIMO可以以各种方式实现。一个极端是集中实现，其中数百个天线部署在小区内的单个位置。另一个极端是全分布式实现，其中分布在整个小区中的数百个单天线远程无线电头端连接到公共基带处理单元，从而形成分布式基站。在这些极端之间的是半分布式实现的相对较少研究的情况，其中多天线远程无线电头端跨小区分布。虽然大规模MIMO的概念已经存在了好几年，但我们对这些系统性能的理解仍然有限。这主要是由于缺乏真实世界的传播模型（特别是对于半分布式实现）以及数学工具，可以暴露用户和基站的不同空间分布的性能趋势，这两者都被称为显着影响这些系统的性能。这项研究的主要目标是开发一种变革性的测量驱动的分析方法，以实现大规模MIMO网络的有效部署，最终通过提高频谱效率带来更好的客户体验，并通过提高能源效率实现更绿色的无线通信。该项目的所有主要成果将通过出版物、教程和行业合作广泛传播。拟议的研究将开发一种全面的测量驱动方法，通过融合多个学科的思想，如通信理论，随机几何，点过程理论和传播建模，对大规模MIMO系统的频谱和能源效率进行分析，产生以下关键创新：（1）随机几何感知的频谱和能量效率度量，以促进跨不同类型的大规模MIMO的基本分析和公平比较，（2）集中式、分布式和半分布式大规模MIMO系统的覆盖分析的新的随机几何方法，（3）在不同类别的传播模型下分布式大规模MIMO系统的信道特性的新结果，（4）广泛的测量活动，（针对大规模MIMO系统定制）使用一种独一无二的信道探测器，（5）用于半确定性大规模MIMO设置的基本上新的信道模型，其将结合路径损耗和色散度量的相关性，除了传统建模的从用户到不同RRH的阴影的相关性之外，以及（6）用于毫米波频率的新的MIMO信道模型。因此，该项目将结合联合收割机强大的空间建模工具，从随机几何与现实世界的大规模MIMO信道模型，比较和对比性能的不同口味的大规模MIMO在现实世界的操作约束，这将直接影响未来的蜂窝网络的设计，操作和管理。

项目成果

Performance Analysis of Channel Extrapolation in FDD Massive MIMO Systems

• DOI: 10.1109/twc.2020.2967711
• 发表时间: 2019-03
• 期刊: IEEE Transactions on Wireless Communications
• 影响因子: 10.4
• 作者: François Rottenberg;Thomas Choi;Peng-Ju Luo;C. Zhang;A. Molisch

Uplink Energy Efficiency of Cell-Free Massive MIMO With Transmit Power Control in Measured Propagation Channels

• DOI: 10.1109/sips52927.2021.00037
• 发表时间: 2021-08
• 期刊: 2021 IEEE Workshop on Signal Processing Systems (SiPS)
• 作者: Thomas Choi;Masaaki Ito;I. Kanno;Takeo Oseki;K. Yamazaki;A. Molisch

How Many Antennas Do We Need for Massive MIMO Channel Sounding? - Validating Through Measurement

大规模 MIMO 信道探测需要多少天线？

• 发表时间: 2019
• 期刊: IEEE APS Symposium
• 作者: Choi, T.;Rottenberg, F.;Luo, P.;Zhang, J.;Molisch, A. F.
• 通讯作者: Molisch, A. F.

Standardization of Propagation Models for Terrestrial Cellular Systems: A Historical Perspective

• DOI: 10.1007/s10776-020-00500-9
• 发表时间: 2020-10
• 期刊: International Journal of Wireless Information Networks
• 影响因子: 2.5
• 作者: H. Tataria;K. Haneda;A. Molisch;M. Shafi;F. Tufvesson

Using a Drone Sounder to Measure Channels for Cell-Free Massive MIMO Systems

使用无人机测深仪测量无蜂窝大规模 MIMO 系统的信道

• DOI: 10.1109/wcnc51071.2022.9771649
• 发表时间: 2022
• 期刊: IEEE WCNC
• 作者: Choi, Thomas;Gomez-Ponce, Jorge;Bullard, Colton;Kanno, Issei;Ito, Masaaki;Ohseki, Takeo;Yamazaki, Kosuke;Molisch, Andreas F.
• 通讯作者: Molisch, Andreas F.