Geometry-Based Stochastic Model and Statistical Characteristic Analysis of Cell-Free Massive MIMO Channels

Abstract

Cell-free massive multi-input multi-output (MIMO) systems exhibit many characteristics that differ from those of traditional centralized massive MIMO systems, and there are still research gaps in the modeling of cell-free massive MIMO channels. In this paper, a geometry-based stochastic model (GBSM) that combines the double-ring model and hemisphere model to comprehensively consider the distribution of scatterers in the environment was proposed for cell-free massive MIMO channels. Combined with the line-of-sight (LoS) path, single scattering path, and double scattering path components, the channel matrix between the access points (APs) and the user was derived. The proposed model fully considers geometric parameters such as the arrival/departure direction, elevation angle, time delay, and distance, which can accurately characterize the channel. Then, we proved that the traditional channel model, standard block-fading model, and spatial basis expansion model (SBEM) adopted in a cell-free massive MIMO system could not describe the nonstationarity in the space, time, and frequency domains, whereas the proposed GBSM could. Statistical characteristics of the channel were analyzed, including the space cross-correlation function (CCF), time autocorrelation function (ACF), Doppler power spectral density (PSD), level crossing rate (LCR), and average fade duration (AFD). Then, we investigated the proposed model by simulating the space CCF, time ACF, Doppler PSD, LCR, and AFD under the conditions of two different scatterer densities. Through simulations and analyses, some new features of cell-free massive MIMO channels were identified, providing a theoretical basis for in-depth research on cell-free massive MIMO systems. Finally, the measurement-based scenario and the WINNER II channel model are compared to demonstrate that the GBSM is more practical to characterize real cell-free massive MIMO channels.