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Modeling of Spatially Correlated Geometry-Based Stochastic Channels

Massive MIMO, 3D beamforming and beam tracking strategies for mobile users are among the key strategies for the 5th generation of mobile cellular networks. Their investigation requires channel models that are spatially consistent and evolve smoothly over time. State-of-the-art channel models, such as, 3GPP SCM, WINNER and the 3GPP 3D channel model, do not consider the time evolution and are relevant only for drop based simulations. In this paper we propose two methods to model spatially correlated channels; first, by introducing spatial correlation to LOS/NLOS propagation and indoor/outdoor state of a user, and second, by introducing spatial correlation to the small scale parameters that represent short-term fading characteristics. Our results exhibit realistic behavior of users that move through the network, in terms of LOS/NLOS and indoor/outdoor states and preserve the statistics of the channel model.