# Simplified Ray Tracing for the Millimeter Wave Channel: A Performance Evaluation

arXiv: https://arxiv.org/abs/2002.09179 · HTML: https://mlsanity.com/paper/2002.09179/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Feb 2020.

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

- [On the Convergence Time of Federated Learning Over Wireless Networks Under Imperfect CSI](https://mlsanity.com/paper/2104.00331/) (2021)
- [Self-Supervised Radio-Visual Representation Learning for 6G Sensing](https://mlsanity.com/paper/2111.02887/) (2021)

## Abstract (arXiv)

Millimeter-wave (mmWave) communication is one of the cornerstone innovations of fifth-generation (5G) wireless networks, thanks to the massive bandwidth available in these frequency bands. To correctly assess the performance of such systems, however, it is essential to have reliable channel models, based on a deep understanding of the propagation characteristics of the mmWave signal. In this respect, ray tracers can provide high accuracy, at the expense of a significant computational complexity, which limits the scalability of simulations. To address this issue, in this paper we present possible simplifications that can reduce the complexity of ray tracing in the mmWave environment, without significantly affecting the accuracy of the model. We evaluate the effect of such simplifications on link-level metrics, testing different configuration parameters and propagation scenarios.