The aim of this book is to delineate the challenges faced by new generation mobile networks, such as 5G and forthcoming 6G, and introduce the concept of addressing these challenges through the development of a novel Distributed AI (DAI) framework. The book proposes a distributed AI approach to handle these complexities effectively.
Distributed Artificial Intelligence for 5G/6G Communications: Frameworks with Machine Learning aims to provide a comprehensive understanding of the proposed DAI framework, its architecture, implementation, and application in the context of D2D communication in 5G and beyond networks. It showcases how the framework can enhance decision-making, control, and communication performance while considering both static and dynamic network environments. The book delves into the advantages of D2D communication, highlighting how it transcends licensed frequency bands and bypasses the cellular network, leading to improved network metrics such as spectral efficiency, energy efficiency, data rates, and interference management. It concludes by emphasizing that the DAI framework can offer enhanced network control, reduced signaling overhead, and efficient decision-making while capitalizing on existing implementations to tackle various challenges across the 5G and 6G landscape.
This book is intended for professionals that specialize in designing, implementing, and maintaining communication networks such as telecommunications/ communication engineers, wireless engineers. The book's emphasis on incorporating AI and ML techniques in the proposed framework also makes it of interest to computer and software engineers working in artificial intelligence and machine learning engineers.
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Postgraduate and Professional Reference
Illustrationen
5 s/w Photographien bzw. Rasterbilder, 53 s/w Zeichnungen, 35 s/w Tabellen, 58 s/w Abbildungen
35 Tables, black and white; 53 Line drawings, black and white; 5 Halftones, black and white; 58 Illustrations, black and white
Maße
Höhe: 240 mm
Breite: 161 mm
Dicke: 19 mm
Gewicht
ISBN-13
978-1-032-74435-3 (9781032744353)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Dr. Iacovos Ioannou is a researcher affiliated with CYENS and the Networks Research Laboratory at the University of Cyprus. His research focuses on emerging fields including mobile and Internet of Things (IoT) network security, 5G and 6G wireless communications, and the incorporation of Distributed Artificial Intelligence (DAI), Artificial Intelligence (AI), and Machine Learning (ML) in device-to-device (D2D) communications. His areas of competence encompass a wide range of activities, including the analysis, development, installation, and maintenance of IT systems and applications.
Dr. Prabagarane Nagaradjane is an Associate Professor with the Department of Electronics and Communication Engineering, SSN Institutions. He received M.Tech and Ph.D. degrees in ECE from Pondicherry Engineering College, Pondicherry (Central) University. Before this, he was with HCL Info Systems for a brief period of two years. His research interests include various aspects of wireless communications, especially concerning signal processing for wireless and broadband communications and AI/ML applications in wireless communications.
Dr. Vasos Vassiliou is an Associate Professor with the Computer Science Department of the University of Cyprus and the co-director of the Networks Research Laboratory (NetRL) at UCY (founded by Prof. A. Pitsillides). He is also the Group Leader of the Smart Networked Systems Research Group of the RISE Center of Excellence on Interactive Media, Smart Systems and Emerging Technologies, situated in Nicosia, Cyprus. Dr. Vassiliou has been appointed by the Senate of the University of Cyprus to the Board of Directors of CYNET, the National Research and Educational Network, where he has served as the Chair since 2016.
Dr. Andreas Pitsillides is Emeritus Professor in the Department of Computer Science, University of Cyprus and Visiting Professor Department of Electrical & Electronic Engineering Science, University of Johannesburg. He was co-director of the Networks Research Laboratory (UCY) and was appointed Visiting Professor at the University of the Witwatersrand (Wits), School of Electrical and Information Engineering. His broad research interests include communication networks, including Programmable Wireless Environments enabled by Software Defined Metamaterials (Reconfigurable Intelligent Surfaces), Nanonetworks (bio and e-m), the Internet- of Things, Smart Systems (e.g. Smart Grid), Smart Spaces (e.g. Home, City), and e-health.
Dr. Christophoros Christophorou is an Assistant Professor in Computing at the School of Sciences of the University of Central Lancashire (UCLan) Cyprus. He is also a Senior Researcher at the Smart Networked Systems Research Group of the CYENS - Center of Excellence. Mr. Christophorou completed his undergraduate and graduate studies at the University of Cyprus (B.Sc. in Computer Science and M.Sc. in Advanced Computer Technologies, 2002 and 2005, respectively). He received his Ph.D., also at the University of Cyprus, in the area of Mobile Networks, in 2011. His main research interests and expertise are mostly concentrated in the Mobile Telecommunications and Networking research fields with major interest in 5G/6G Mobile Cellular Networks area. These include 5G/6G Network architectures and Key Technologies, Edge and far-edge Computing, Distributed Artificial Intelligence (DAI) in Wireless Networks, and Network Resource Management and Optimization.
1- Introduction
2- Background, Literature Review and Related Work
3- A Novel DAI Framework and BDI Extended Agents
4- Implementation Specifics of the DAI Framework for D2D Communication
5- Example Plans of the DAI framework/BDIx agents to Satisfy D2D Challenges
6- DAI Framework for Addressing the D2D Mode Selection Challenge
7- DAI Framework Evaluation for the D2D Mode Selection Challenge Realisation
8- Future Directions and Application Areas
