期刊
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
卷 69, 期 12, 页码 14212-14224出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2020.3037199
关键词
Array-variant angular and delay distributions; massive MIMO; non-stationary channel models; statistical properties; transformation method
资金
- National Key R&D Program of China [2018YFB1801101]
- National Natural Science Foundation of China [61960206006]
- Frontiers Science Center for Mobile Information Communication and Security
- High Level Innovation and Entrepreneurial Research Team Program in Jiangsu
- High Level Innovation and Entrepreneurial Talent Introduction Program in Jiangsu
- Research Fund of National Mobile Communications Research Laboratory, Southeast University [2020B01]
- Fundamental Research Funds for the Central Universities [2242020R30001]
- EU H2020 RISE TESTBED2 project [872172]
- EU H2020 5G Wireless project [641985]
In this article, we propose a transformation method to model space-time-variant (STV) two-dimensional non-stationary wideband massive multiple-input multiple-output (MIMO) channels. This method enables us to obtain the STV joint probability density function of the time of arrival and angle of arrival (AOA) at any time instant and antenna element of the array from a predefined configuration of the scatterers. In addition, we introduce a simplified channel modeling approach based on STV parameters of the AOA distribution and demonstrate that key statistical properties of massive MIMO channels, such as the STV temporal autocorrelation function and Doppler power spectral density, can be derived in closed form. As examples of application, we study multiple array-variant properties of three widely-used geometry-based stochastic models (GBSMs): the Unified Disk, Ellipse, and Gaussian scattering models. Furthermore, we present numerical and simulation results of the statistical properties of these three GBSMs and compare them with those obtained using the conventional spherical wavefront approach. We point out possible limitations of the studied channel models to properly represent massive MIMO channels.
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