Bayesian EM Digital Twins Channel Estimation

TL;DR

This paper introduces a Bayesian channel estimation method utilizing Electromagnetic Digital Twin information, achieving significant NMSE improvements, spectral efficiency comparable to ideal conditions, and reduced pilot requirements at low SNR.

Contribution

It presents a novel Bayesian EM-DT-based channel estimation technique that outperforms conventional methods by leveraging environment-aware prior information.

Findings

Over 10 dB NMSE gain compared to traditional methods

Spectral efficiency comparable to ideal channel state information

Reduced pilot usage at low SNR levels

Abstract

This letter proposes a Bayesian channel estimation method that leverages on the a priori information provided by the Electromagnetic Digital Twin's (EM-DT) representation of the environment. The proposed approach is compared with several conventional techniques in terms of Normalized Mean Square Error (NMSE), spectral efficiency, and number of pilots. Simulations prove more than $10\,$dB gain in NMSE and a spectral efficiency comparable to that of the ideal channel state information, for different signal-to-noise ratio (SNR) values. Additionally, the Bayesian EM-DT-empowered channel estimation enables a remarkable pilot reduction compared to maximum likelihood methods at low SNR.