Machine and Deep Learning Techniques in Wireless and Satellite Communication Networks

A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: closed (20 January 2024) | Viewed by 214

Special Issue Editor


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Guest Editor
School of Electrical and Computer Engineering, National Technical University of Athens, 15780 Athens, Greece
Interests: communications; wireless communications; radio communications; communications theory; modulations and coding; satellite & space communications; vehicular technology; antennas and propagation; gigabit networking; computer communications; systems and protocols; artificial intelligence techniques in communication data and networks.
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Special Issue Information

Dear Colleagues,

The standardization of 5G wireless networks (including a non-terrestrial component) is currently underway. Moreover, researchers have also focused on what 6G will become, making progress on designing the new architecture. The applications of artificial intelligence (AI), machine learning (ML) and deep learning (DL) techniques in wireless and satellite communications networks have drawn significant attention recently and are applied in the design of 5G wireless networks as well as used as built in functionalities in 6G networks. ML and DL techniques enable wireless communications in order to fulfill increasing and diverse requirements across a large range of application scenarios. Additionally, there are optimization algorithms for the solution of complex wireless networks. On the one hand, training a complex deep learning model is time consuming and can take hours, days, or even weeks. Their cooperation with an optimization algorithm directly affects the model’s training efficiency and finally its performance. On the other hand, understanding the principles of different optimization algorithms and the role of their hyperparameters will enable us to tune the hyperparameters in a targeted manner to improve the performance of deep learning models. In the proposed Special Issue, we expect papers on the above subjects and on classical wireless scenarios, such as channel modeling; physical layer up intelligent resource allocation algorithms and the consideration of the ML and DL techniques as services.

Topics of interest include but are not limited to the following:

  • ML, DL techniques for Physical Layer Design including signal detection, classification and compression;
  • ML, DL techniques for spectrum sensing and positioning;
  • ML, DL techniques for channel modeling, radio propagation, estimation and prediction;
  • ML, DL techniques for resource allocation and wireless and satellite networks optimization;
  • ML, DL techniques for new emerging applications toward 6G (including intelligent reflection surface, unmanned aerial vehicles, the Internet of Things, etc.)
  • ML, DL techniques for vehicular networks;
  • Distributed machine learning/federated learning and communications;
  • AI, ML and DL for Satellite Communications including GEO, MEO and LEO Constellations;
  • AI, ML and DL for Satellite Communications including UAVs and Micro Satellite Systems;
  • AI, ML and DL for Cognitive Radio Communications and Networks.

Prof. Dr. Athanasios D. Panagopoulos
Guest Editor

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. Future Internet 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 1600 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

  • artificial intelligence techniques for wireless and satellite communications
  • machine and deep learning for wireless and satellite communication
  • deep reinforcement learning
  • 5G/6G wireless networks

Published Papers

There is no accepted submissions to this special issue at this moment.
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