An Overview of Machine Learning Techniques for Radiowave Propagation Modeling
Aristeidis Seretis, Costas D. Sarris
Abstract
We give an overview of recent developments in the modeling of radiowave propagation, based on machine learning (ML) algorithms. We identify the input and output specification and the architecture of the model as the main challenges associated with ML-driven propagation models. Relevant papers are discussed and categorized based on their approach to each of these challenges. Emphasis is given on presenting the prospects and open problems in this promising and rapidly evolving area.
Topics & Concepts
Computer scienceArtificial intelligenceMachine learningMillimeter-Wave Propagation and ModelingRadio Wave Propagation StudiesIndoor and Outdoor Localization Technologies