Classification and Comparison of Massive MIMO Propagation Channel Models

Considering great benefits brought by massive multiple-input–multiple-output (MIMO) technologies in the Internet of Things (IoT), it is vital importance to analyze new MIMO channel characteristics and develop corresponding models. In literature, various models have been proposed classified with different but confusing methods, i.e., physical versus analytical method deterministic stochastic method. To a better understanding usage models, this work summarizes classification methods presents an up-to-date unified framework, artificial intelligence (AI)-based predictive classical nonpredictive which further clarify combine methods. Furthermore, measurement campaigns are reviewed summarize characteristics. Recent advances modeling surveyed. addition, typical elaborated compared, include correlation-based model (CBSM), geometry-based (GBSM), beam-domain (BDCM). Finally, future challenges given.