OnRMap: An Online Radio Mapping Approach for Large Intelligent Surfaces

TL;DR

OnRMap is an online radio mapping technique that accurately localizes active users and environmental elements using large intelligent surfaces, enabling real-time sensing without offline scanning, with improved accuracy over offline methods.

Contribution

The paper introduces OnRMap, a novel online radio mapping approach that performs real-time sensing and localization without offline calibration, suitable for dynamic environments.

Findings

Higher localization accuracy than offline methods

Moderate reduction in detection rate compared to offline approaches

Effective in environments with changing spatial layouts

Abstract

We introduce OnRMap, an online radio mapping (RMap) approach for the sensing and localization of active users (AUs), devices that are transmitting radio signals, and passive elements (PEs), elements that are in the environment and are illuminated by the AUs' radio signals. OnRMap processes the signals received by a large intelligent surface and produces a radio map (RM) of the environment based on signal processing techniques. The method then senses and locate the different elements without the need for offline scanning phases, which is important for environments with frequently changing spatial layouts. Empirical results demonstrate that OnRMap presents a higher localization accuracy than an offline method, but the price paid for being an online method is a moderate reduction in the detection rate.