A Spatially Consistent Geometric D2D Small-Scale Fading Model for Multiple Frequencies

The 3rd generation partnership project (3GPP) new radio (NR) channel model introduced spatial consistency and a correlation model for multiple frequencies. Future extensions of this model will incorporate mobility at both ends of the link. These features are essential for many emerging wireless technologies in the 5G era. However, the existing small-scale-fading (SSF) model does not integrate these features coherently. To solve this problem, we propose a new SSF model that seamlessly integrates with the remaining NR model and allows the simultaneous simulation of all three features. We demonstrate this integration by showing that the output of the new SSF model agrees well with large-scale fading (LSF) parameter distributions provided by 3GPP. This enables the simulation of new wireless technology proposals that were difficult to realize with existing geometry-based stochastic channel models (GSCMs).

I. Introduction

GSCMs are a well-established tool to model wireless propagation channels. They consist of two main components: a stochastic part that generates a random propagation environment, and a deterministic part that lets transmitters (TXs) and receivers (RXs) interact with this environment. To predict the wireless system performance, the random environment must fulfill certain statistical properties which are determined by measurements. These properties are generated by the so-called LSF model. A subsequent SSF model generates individual multipath components (MPCs) for each mobile terminal (MT). GSCMs became widely used by the 3GPP which required standardized models to evaluate new technology proposals. This was provided by the spatial channel model (SCM) in 2003 [1]. Since then, this model has undergone many iterations to support new features of the fast evolving wireless world. However, the SSF model has not been significantly enhanced which leads to incompatibilities with some newly introduced features of the NR model [2].