Special Issue "Machine Learning for Wireless Networks - Recent Advances and Future Trends"

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".

Deadline for manuscript submissions: 31 May 2021.

Special Issue Editors

Dr. Shankar Kathiresan
Website
Guest Editor
Department of Computer Applications, Alagappa University, Karaikudi - 630 002, India
Interests: healthcare applications; secret image sharing scheme; digital image security; cryptography; internet of things; optimization algorithms
Dr. Deepak Gupta
Website
Guest Editor
Department of Computer Science and Engineering, Maharaja Agrasen institute of Technology (GGSIPU), Delhi 110086, India
Interests: software engineering; software usability; human computer interaction; algorithm computing; soft computing; neural networks; testing
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Dr. Gyanendra Prasad Joshi
Website SciProfiles
Guest Editor
Intelligent Computing and Communication Lab, Sejong University, Sejong 05006, Korea
Interests: Sensor localization, Image Sensors, MAC and routing protocols for wireless sensor networks, cognitive radio Wireless Sensor Networks, RFID system, IoT, smart city, deep learning and digital convergence
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Prof. Dr. Chi-Hua Chen
Website
Guest Editor
College of Mathematics and Computer Science, Fuzhou University, Fuzhou City, Fujian Province, China, No. 2, Xueyuan Road, Minhou County, Fuzhou 350108, China
Interests: Internet of things; machine learning; mobile communications
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Dr. Vicente García-Díaz
Website
Guest Editor
Department of Computer Science, University of Oviedo, 33003 Oviedo, Spain
Interests: machine learning; decision support systems; domain-specific languages; eLearning
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Our society is experiencing a digitization revolution, with a drastic growth of Internet users and connected devices. Next-generation wireless networks should provide ultra-reliable, low-latency communication and intelligently control the internet of things (IoT) devices in real-time scenarios. Wireless network applications like in real-time traffic data, sensor reading from driverless cars, or Netflix entertainment recommendations generate extreme volumes of data that must be collected and processed in real time. These communication requirements and core intelligence can only be achieved through the integration of machine learning techniques in the wireless infrastructure and end-user devices.

In recent times, machine learning algorithms have gained significant interest in the area of wireless networking and communication. Machine learning-driven algorithms and models can enable wireless network analysis and resource management and be of advantage in handling the development in volume of communication and computation for evolving networking applications. Nevertheless, the application of machine learning techniques for heterogeneous wireless networks is still under debate. More endeavors are needed to link the gap between machine learning and wireless networking research.

The objective of this Special Issue is to explore recent advancements in machine learning concepts to address practical challenges in wireless networks. This Special Issue will bring together researchers and academics to present new results in network modeling and architecture, networking applications, security and privacy, resource management, load balancing, and various challenges related to the design for future wireless networks with the help of machine learning.

This Special Issue “Machine Learning for Wireless Networks – Recent Advances and Future Trends” will solicit papers on various disciplines, including but not limited to the following:

  • machine learning algorithms for network scheduling and control;
  • machine learning based energy-efficient networking techniques;
  • machine learning-based network resource allocation and optimization in wireless networks;
  • new supervised machine learning methods for wireless networks; new unsupervised machine learning methods for wireless networks;
  • novel reinforcement learning methods for wireless networks; new optimization methods for machine learning for wireless networks;
  • machine learning-based innovative intelligent computing architecture/algorithms for wireless networks;
  • machine learning based big data analytic frameworks for networking data;
  • machine learning-based intelligent routing algorithms for traffic management in wireless networks;
  • machine learning-based resource allocation for shared/virtualized networks using machine learning;
  • machine learning-based quality of service (QoS) management in wireless networks;
  • nature-inspired algorithms for wireless networks;
  • machine learning-based blockchain for wireless networks; machine learning-based node localization in wireless networks

Dr. Shankar Kathiresan 
Dr. Deepak Gupta
Dr. Gyanendra Prasad Joshi
Prof. Dr. Chi-Hua Chen
Dr. Vicente García-Díaz
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 papers will be 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. Electronics 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 1500 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

  • machine learning
  • deep learning
  • wireless networks
  • optimization
  • routing
  • traffic management
  • big data
  • blockchain
  • energy efficiency

Published Papers

This special issue is now open for submission.
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