Channel Charting in Smart Radio Environments

Maleki, Mahdi, Ayoubi, Reza Agahzadeh, Mizmizi, Marouan, Spagnolini, Umberto

arXiv.org Artificial Intelligence 

--This paper introduces the use of static electromagnetic skins (EMSs) to enable robust device localization via channel charting (CC) in realistic urban environments. We develop a rigorous optimization framework that leverages EMS to enhance channel dissimilarity and spatial fingerprinting, formulating EMS phase profile design as a codebook-based problem targeting the upper quantiles of key embedding metrics--localization error, trustworthiness, and continuity. Through 3D ray-traced simulations of a representative city scenario, we demonstrate that optimized EMS configurations, in addition to significant improvement of the average positioning error, reduce the 90th-percentile localization error from over 60 m (no EMS) to less than 25 m, while drastically improving trustworthiness and continuity. T o the best of our knowledge, this is the first work to exploit Smart Radio Environment (SRE) with static EMS for enhancing CC, achieving substantial gains in localization performance under challenging None-Line-of-Sight (NLoS) conditions. Wireless channel charting (CC) represents a transformative approach to understanding and utilizing the intrinsic properties of wireless communication environments [1].

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