Radio maps characterize quantities of interest in radio communication environments, such as the received signal strength and channel attenuation, at every point of a geographical region. Radio map estimation typically entails interpolative inference based on spatially distributed measurements. In this tutorial article, after presenting some representative applications of radio maps, the most prominent radio map estimation methods are discussed. Starting from simple regression, the exposition gradually delves into more sophisticated algorithms, eventually touching upon state-of-the-art techniques. To gain insight into this versatile toolkit, illustrative toy examples will also be presented.
Cite
@article{arxiv.2202.03269,
title = {Radio Map Estimation: A Data-Driven Approach to Spectrum Cartography},
author = {Daniel Romero and Seung-Jun Kim},
journal= {arXiv preprint arXiv:2202.03269},
year = {2022}
}