Information Theory and AI-Driven Communications
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory, Probability and Statistics".
Deadline for manuscript submissions: 1 March 2026 | Viewed by 5
Special Issue Editors
Interests: information theory; communications; machine learning
Interests: network information theory; statistical decision theory; data compression; security and privacy
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Whilst information theory (IT)-driven communications have led the evolution of mobile communication systems in the recent decades, artificial intelligence (AI)-driven approaches have been demonstrating great potentials in bolstering the future (r)evolutions. However, there is still a lack of theoretical understanding to underpin such a revolutionary thread of integrated IT-/AI-driven communications. This Special Issue aims to present cutting-edge research on (1) transformations of IT-driven communication frameworks and algorithms to AI-driven architectures and models using e.g., learning-to-code, learning-to-optimize, and learning-to-unfold approaches; and (2) theoretical foundations of AI-driven models and algorithms for communications with respect to generalization, robustness, explanation, information security and privacy, and learning theoretical perspectives.
In particular, we welcome contributions that investigate innovative model/data-driven deep learning approaches to digital communications for source/channel coding/decoding, multiuser multi-input multi-output (MIMO) detection, channel estimation/prediction/feedback, multiuser/multicell/cell-free MIMO precoding, interference management, radio resource management, etc. Meanwhile, we encourage studying theoretical guarantees of AI models/algorithms with respect to in-distribution and out-of-distribution generalization across different wireless environments, robustness against network dynamics, channel uncertainties, adversarial attacks, and the wide range of explainability, security, and privacy. Prospective authors are invited to submit original manuscripts on the following topics including, but not limited to, the following:
- Theoretical foundations of AI-driven communications.
- AI-driven transceiver design for multiuser communication systems.
- AI-driven interference management in multicell/cell-free MIMO networks.
- AI-driven radio resource management in wireless networks.
- Generalization analysis of AI-driven communication algorithms.
- Robustness analysis of AI-driven communications algorithms.
- Explainability studies of AI-driven communication algorithms.
- Security and privacy aspects of AI-driven communications.
- The interplay between IT- and AI-driven communications.
We look forward to receiving your contributions.
Prof. Dr. Xinping Yi
Dr. Abdellatif Zaidi
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- AI-driven communications
- information theory
- artificial intelligence
- multi-input multi-output (MIMO)
- channel coding
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