AI for Wireless Communication Systems: From Semantic Communications to 6G
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory, Probability and Statistics".
Deadline for manuscript submissions: 31 January 2027 | Viewed by 710
Editors
Interests: information theory; semantic communication; channel coding; wireless communications; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: information theory; semantic communication; channel coding; combinatorics
Interests: distributed source coding; cell-free massive MIMO; integrated sensing and communication; deep learning; generative model
Special Issue Information
Dear Colleagues,
This Special Issue on "AI for Wireless Communication Systems: From Semantic Communications to 6G" explores the transformative intersection of artificial intelligence (AI) and next-generation wireless networks. As the research focus shifts toward 6G, networks are now required to support emerging architectures, such as cell-free massive MIMO (CF-mMIMO), integrated sensing and communication (ISAC), and reconfigurable intelligent surface (RIS), advancements which introduce new requirements for massive connectivity, low latency, and strict reliability.
Fully unlocking the potential of these complex physical layer architectures requires a paradigm shift in how information is processed and valued. This is where AI serves as the fundamental enabler for the transition toward semantic communications. Moving beyond the traditional Shannon framework of bit-exact delivery, semantic-aware networks focus on only extracting and transmitting the meaning, intent, or specific features required for a downstream task. Deep learning architectures facilitate this by encoding relevant semantic information at the source and recovering knowledge at the destination. By optimizing the transmission for specific tasks rather than raw data reconstruction, this task-oriented approach is essential in offering a sustainable solution for next-generation networks.
This Special Issue seeks the submission of original research exploring how machine learning models can be leveraged to design these semantic frameworks and integrate them seamlessly with 6G physical and network layers.
Dr. Yinfei Xu
Dr. Qi Cao
Dr. Shu Xu
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 250 words) can be sent to the Editorial Office for assessment.
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-anonymized 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
- semantic communications
- semantic-aware networks
- 6G wireless communications
- task-oriented communications
- deep learning
- AI-native network architecture
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