5G Positioning and Mapping with Diffuse Multipath

TL;DR

This paper introduces a tensor-based channel estimation method for 5G mmWave systems that accurately estimates diffuse multipath components, enabling effective positioning and mapping even without clear line-of-sight paths.

Contribution

A novel non-parametric tensor-based approach for channel estimation that works with diffuse multipath in 5G mmWave environments.

Findings

Accurately estimates channel parameters in diffuse multipath scenarios.

Enables positioning and mapping without specular components.

Demonstrates effectiveness through simulation results.

Abstract

5G mmWave communication is useful for positioning due to the geometric connection between the propagation channel and the propagation environment. Channel estimation methods can exploit the resulting sparsity to estimate parameters(delay and angles) of each propagation path, which in turn can be exploited for positioning and mapping. When paths exhibit significant spread in either angle or delay, these methods breakdown or lead to significant biases. We present a novel tensor-based method for channel estimation that allows estimation of mmWave channel parameters in a non-parametric form. The method is able to accurately estimate the channel, even in the absence of a specular component. This in turn enables positioning and mapping using only diffuse multipath. Simulation results are provided to demonstrate the efficacy of the proposed approach.