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Special Issue "Deep Reinforcement Learning in Communication Systems and Networks"

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Communications".

Deadline for manuscript submissions: 31 October 2022 | Viewed by 177

Special Issue Editors

Dr. Gianmarco Romano
E-Mail Website
Guest Editor
Department of Engineering, University of Campania “Luigi Vanvitelli”, via Roma, 29, 81031 Aversa, CE, Italy
Interests: signal processing; wireless communications; wireless sensor networks; 5G; MIMO; OFDM; smart-grids; software defined radio
Special Issues, Collections and Topics in MDPI journals
Dr. Giovanni Di Gennaro
E-Mail Website
Guest Editor
Department of Engineering, University of Campania “Luigi Vanvitelli”, via Roma, 29, 81031 Aversa, CE, Italy
Interests: machine learning; artificial neural network; deep learning; reinforcement learning; signal processing; image processing; time series analysis; natural language processing
Dr. Amedeo Buonanno
E-Mail Website
Guest Editor
ENEA - Department of Energy Technologies and Renewable Energy Sources, P.le E. Fermi, 1 (Loc. Granatello), 80055 Portici, NA, Italy
Interests: machine learning; artificial neural network; deep learning; reinforcement learning; signal processing; image processing; time series analysis; energy forecasting; smart-grids

Special Issue Information

Dear Colleagues,

Deep reinforcement learning (DRL), the combination of reinforcement learning and deep learning, has emerged as a viable solution for overcoming limitations due to large state–action spaces and improving the learning speed and performances. DRL algorithms have been developed to address issues and challenges arising in a variety of fields, such as robotics, computer vision, and speech recognition, their application potentially able to extend to solve any optimization problem in a general way by searching for a solution through interactions with the environment.

Recently, DRL algorithms have been developed to address communication system and network problems to tackle complex optimization tasks that cannot be solved efficiently with traditional optimization techniques. For example, wireless networks represent a complex dynamic environment, where the efficient use of spectrum utilization, power control, interference coordination and beamforming is needed to cope with the increasing demand of a large number of devices and higher data rates in future communication systems.

This Special Issue invites prospective authors to submit original contributions regarding applications of deep reinforcement learning algorithms, with a specific focus on communication systems and networks.

Dr. Gianmarco Romano
Dr. Giovanni Di Gennaro
Dr. Amedeo Buonanno
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. Sensors is an international peer-reviewed open access semimonthly 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 2400 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

  • deep reinforcement learning
  • communications
  • wireless networks
  • 5G/6G
  • spectrum access
  • intelligent reflecting surface
  • Internet of Things (IoT)
  • heterogeneous networks (HetNets)
  • unmanned aerial vehicle (UAV)
  • vehicular ad hoc networks

Published Papers

This special issue is now open for submission.
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