Efficient Sum-of-Sinusoids based Spatial Consistency for the 3GPP New-Radio Channel Model

TL;DR

This paper introduces an efficient sum-of-sinusoids method to model spatial consistency in 3GPP New-Radio channels, enabling accurate dual-mobility simulations across multiple dimensions with improved autocorrelation control.

Contribution

It extends the sum-of-sinusoids model to higher spatial dimensions and proposes a new coefficient calculation method for better autocorrelation control.

Findings

Achieves four times better approximation accuracy than previous models.

Effective in 2, 3, and 6 spatial dimensions.

Enables simulation of complex mobility scenarios previously infeasible.

Abstract

Spatial consistency was proposed in the 3GPP TR 38.901 channel model to ensure that closely spaced mobile terminals have similar channels. Future extensions of this model might incorporate mobility at both ends of the link. This requires that all random variables in the model must be correlated in 3 (single-mobility) and up to 6 spatial dimensions (dual-mobility). Existing filtering methods cannot be used due to the large requirements of memory and computing time. The sum-of-sinusoids model promises to be an efficient solution. To use it in the 3GPP channel model, we extended the existing model to a higher number of spatial dimensions and propose a new method to calculate the sinusoid coefficients in order to control the shape of the autocorrelation function. The proposed method shows good results for 2, 3, and 6 dimensions and achieves a four times better approximation accuracy compared to the existing model. This provides a very efficient implementation of the 3GPP proposal and enables the simulation of many communication scenarios that were thought to be impossible to realize with geometry-based stochastic channel models.