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

arXiv: https://arxiv.org/abs/1808.04659 · HTML: https://mlsanity.com/paper/1808.04659/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 14 Aug 2018.

## Built on by (most cited first, 2 of 2)

- [Large Vision Model-Enhanced Digital Twin with Deep Reinforcement Learning for User Association and Load Balancing in Dynamic Wireless Networks](https://mlsanity.com/paper/2410.07611/) (2024)
- [Map2Traj: Street Map Piloted Zero-shot Trajectory Generation with Diffusion Model](https://mlsanity.com/paper/2407.19765/) (2024)

## Abstract (arXiv)

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.