Channel Correlation Matrix Extrapolation Based on Roughness Calibration of Scatterers

TL;DR

This paper introduces a novel method to spatially extrapolate the channel correlation matrix by calibrating scatterer roughness parameters, enabling accurate predictions across different areas and frequency domains.

Contribution

It presents a new approach to estimate CCM in unmeasured areas using roughness calibration and ray tracing, improving channel modeling accuracy.

Findings

Effective CCM extrapolation between different areas.

Accurate CCM prediction across frequency domains.

Calibration-based method enhances channel modeling.

Abstract

To estimate the channel correlation matrix (CCM) in areas where channel information cannot be collected in advance, this paper proposes a way to spatially extrapolate CCM based on the calibration of the surface roughness parameters of scatterers in the propagation scene. We calibrate the roughness parameters of scene scatters based on CCM data in some specific areas. From these calibrated roughness parameters, we are able to generate a good prediction of the CCM for any other area in the scene by performing ray tracing. Simulation results show that the channel extrapolation method proposed in this paper can effectively realize the extrapolation of the CCM between different areas in frequency domain, or even from one domain to another.