Next-Generation Wireless Networks Meet Advanced Machine Learning Applications
Core Reference Title

Next-Generation Wireless Networks Meet Advanced Machine Learning Applications

Ioan-Sorin Comşa (Brunel University London, UK) and Ramona Trestian (Middlesex University, UK)
Release Date: January, 2019|Copyright: © 2019 |Pages: 356
ISBN13: 9781522574583|ISBN10: 1522574581|EISBN13: 9781522574590|DOI: 10.4018/978-1-5225-7458-3


The ever-evolving wireless technology industry is demanding new technologies and standards to ensure a higher quality of experience for global end-users. This developing challenge has enabled researchers to identify the present trend of machine learning as a possible solution, but will it meet business velocity demand?

Next-Generation Wireless Networks Meet Advanced Machine Learning Applications is a pivotal reference source that provides emerging trends and insights into various technologies of next-generation wireless networks to enable the dynamic optimization of system configuration and applications within the fields of wireless networks, broadband networks, and wireless communication. Featuring coverage on a broad range of topics such as machine learning, hybrid network environments, wireless communications, and the internet of things; this publication is ideally designed for industry experts, researchers, students, academicians, and practitioners seeking current research on various technologies of next-generation wireless networks.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Cloud-Support Communications
  • Cognitive Radio Networks
  • Cooperative/Distributed Coding
  • Hybrid Network Environments
  • Intelligent Systems
  • Internet of Things (IoT)
  • Machine Learning
  • Telecommunications
  • Wireless Communications
  • Wireless Sensor Networks

Table of Contents and List of Contributors

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Author(s)/Editor(s) Biography

Dr. Ioan-Sorin Comsa is a Research Assistant in 5G radio resource scheduling at Brunel University, London, UK. He was awarded the B.Sc. and M.Sc. degrees in Telecommunications from the Technical University of Cluj-Napoca, Romania in 2008 and 2010, respectively. He received his Ph.D. degree from the Institute for Research in Applicable Computing, University of Bedfordshire, UK in June 2015. He was also a Ph.D. Researcher with the Institute of Complex Systems, University of Applied Sciences of Western Switzerland. Since 2015, he worked as a Research Engineer at CEA-LETI in Grenoble, France. His research interests include intelligent radio resource and QoS management, reinforcement learning, data mining, distributed and parallel computing, adaptive multimedia delivery in heterogeneous wireless networks.
Ramona Trestian is a Lecturer with the Computer and Communications Engineering Department, School of Science and Technology, Middlesex University, London, UK. She was previously an IBM-IRCSET Exascale Postdoctoral Researcher with the Performance Engineering Laboratory (PEL) at Dublin City University (DCU), Ireland since December 2011. She was awarded the PhD from Dublin City University in March 2012 and the B.Eng. degree in Telecommunications from the Electronics, Telecommunications, and the Technology of Information Department, Technical University of Cluj-Napoca, Romania in 2007. She has published in prestigious international conferences and journals and has two edited books. She is a reviewer for international journals and conferences and an IEEE member. Her research interests include mobile and wireless communications, multimedia streaming, handover and network selection strategies, and software-defined networks.