On Massive Antenna Channel Models with Dependent Fading: Theory and Experiments

The performance of massive MIMO wireless communication links depends on the spatial statistics of the underlying wireless channel. While in literature, it is often assumed that MIMO channels are either independent or follow a correlation model according to the Kronecker structure, theory as well as measurements suggest that a more detailed view on the spatial dependency structure is required to design efficient MIMO communication links. The resource efficient design of massive MIMO systems is very relevant for the B5G and 6G generations of cellular and WiFi networks. In this paper, we propose a dependency model for the spatial channel gains in massive MIMO links. In particular, we show the limitations of the state of the art Kronecker-based correlation model, and propose a copula-based model. For two current beamforming strategies, selection combining and maximum ratio combining, we completely characterize the impact of the spatial dependency on the outage probability. In selection combining, the impact is clear, and less dependency improves outage performance. In maximum ratio combining, there is a dichotomy: for low outage probabilities (below 0.5), less dependency improves performance, while for high outage probabilities (above 0.5), more dependency improves performance. We compare our proposed model with channel measurements obtained from our massive MIMO prototyping system and show that our spatial dependency model can well describe the measurements. Finally, the predicted performance behavior is verified by the measurements. The results indicate that a fine granular model for channel dependency can better predict outage performance.