Machine Learning and Cognitive Computing for Mobile Communications and Wireless Networks

in Special Issue   Posted on June 8, 2020 

Information for the Special Issue

Submission Deadline: Thu 15 Oct 2020
Journal Impact Factor : 1.061
Journal Name : Wireless Personal Communications
Journal Publisher:
Website for the Special Issue:
Journal & Submission Website:

Special Issue Call for Papers:

Recently the communication and network technology has witnessed rapid development. Numerous information services and applications have been developed globally. These technologies have high impact on the society and the way people are leading their lives. The advancement in technology has undoubtedly improved the quality of service and user experience yet a lot needs to be still done. Some areas that still need improvement include seamless wide-area coverage, high-capacity hot-spots, low-power massive-connections, low-latency and high-reliability and so on. Thus, it is highly desirable to develop smart technologies for communication to improve the overall services and management of wireless communication.

Machine learning and cognitive computing have converged to give some ice breaking solutions for smart machines. With these two technologies coming together the machines can acquire the ability to reason similar to human brain. The research area of machine learning and cognitive computing cover many fields like psychology, biology, signal processing, physics, information theory, mathematics, and statistics that can be used effectively for topology management. Therefore, the utilization of machine learning techniques like data analytics and cognitive power will lead to better performance of communication and wireless systems.

The topics of interest include but are not limited to:

  • Machine  Learning  for  mobile communication & Wireless network system
  • Machine learning architecture and framework 
  • Machine learning for physical layer design 
  • Deep Reinforcement Learning for Wireless Networks 
  • Data analytics and behavior prediction for communications\networks
  • Machine Learning -based testbed, performance evaluation for communications\networks
  • Machine Learning -based security and privacy protection for communications\networks
  • Spectrum-Aware Mobile Computing
  • Wireless Technology in Internet of Things (IoT)
  • Infrastructure in Mobile Opportunistic Networks
  • Spectrum allocation in Cognitive radio
  • Cognitive Computing: Architecture, Technologies and Intelligent Applications 
  • Cognitive computing for  smart communications
  • Cognitive computing for   Wireless network networks
  • Cognitive Radio Network Technologies and Applications
  • Cooperative and Cognitive Network
  • Emerging Wireless Communication and Network Technologies
  • Architectures and Protocols for Next Generation Cognitive Networking

Submission deadline: October 15, 2020
First-round peer review due: November 30, 2020
Revision due: December 30, 2020
Final manuscript due: January 15, 2021Guest Editors
Dr. Krishna Kant Singh (Lead Guest Editor)
[email protected]
Associate Professor, Department of ECE, KIET Group of institutions, Ghaziabad, India

Dr. Seyedali (Ali) Mirjalili
[email protected]
Director, Centre for Artificial Intelligence Research and Optimization ,Torrens University Australia

Dr. Hari Mohan Pandey
[email protected]
Department of Computer Science, Edge Hill University, UK

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