On the spatial consistency of stochastic and map-based 5G channel models

Abstract

The 5th Generation (5G) of wireless mobile communication systems is currently the focus of many research projects and standardization bodies, such as the 3rd Generation Partnership Project (3GPP). Accurate modeling of the radio propagation channel is important for evaluating the performance of candidate technologies for 5G. However, the state-of-the-art radio channel models, such as the 3GPP 3D channel model, are not appropriate for analyzing all use-cases and scenarios commonly considered for 5G mainly due to its inherent stochastic nature. In particular, the difficulty in dealing with long-term spatial consistency and lack of correlation of small-scale parameters motivates using channel models based on ray-tracing. In fact, channel models that provide spatially consistent observations are of fundamental importance in assessing the performance of multiuser and massive MIMO schemes, by taking into account the spatial correlation of small-scale parameters, as well as of continuous ultra-dense networks (UDNs). This paper shows, by means of extensive numerical results, that the 3GPP 3D channel model consistently underestimates the achievable SIR in LoS multiuser MISO settings. However, in NLoS scenarios and urban micro-cell deployments, the 3GPP 3D channel model significantly overestimates the SIR experienced by the users. Hence, the achievable performance of massive MIMO schemes and continuous UDNs can only be assessed with channel models that take into account the spatial correlation of small-scale parameters.