Artificial Intelligence in Radio Channel Modelling: Progress and Challenges
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".
Deadline for manuscript submissions: 31 December 2025 | Viewed by 88
Special Issue Editors
Interests: wireless communications; channel modelling; channel measurements
Special Issues, Collections and Topics in MDPI journals
Interests: wireless communications; channel modelling; channel measurements
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The definition and standardization of future IMT-2030 systems (6G and beyond) requires multi-dimensional reference models capable of accurately describing wave propagation characteristics, interference patterns, and the dynamic nature of radio channels. Modelling radio channels at millimetre-wave and terahertz frequency bands poses significant challenges due to the special propagation characteristics at these frequencies. This has led researchers to explore innovative methodologies that address the limitations of traditional models based on stochastic and deterministic approaches.
Artificial intelligence (AI), particularly machine learning and deep learning, has emerged as a transformative approach to radio channel modelling. By leveraging its ability to learn patterns from large data sets, AI provides a powerful tool to analyze and model complex, non-linear phenomena that are difficult to capture using traditional methods. In addition to improving model accuracy, AI also enables real-time adaptability, a critical capability in highly dynamic communication environments.
This Special Issue aims to provide a comprehensive view of how AI can significantly improve our ability to understand, predict, and optimize radio channels, addressing the challenges and taking advantage of the opportunities offered by this exciting technology. Key topics of interest for this Special Issue include, but are not limited to, the following:
- Processing large channel measurement records;
- Identification of propagation patterns;
- Estimation of channel parameters;
- Interpretability of AI-based models;
- Channel estimation and prediction;
- Inherent challenges of AI in channel modelling;
- Channel modelling with application to advanced techniques based on extreme-MIMO and beamforming.
Prof. Dr. Lorenzo Rubio
Prof. Dr. Vicent Miquel Rodrigo Peñarrocha
Guest Editors
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Keywords
- artificial intelligence
- machine learning
- deep learning
- radio wave propagation
- wireless channels
- channel modelling
- channel measurements
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