Experimentation in 5G and beyond Networks: State of the Art and the Way Forward

doi:10.3390/books978-3-7258-0045-2

Reprint

Download Flyer

Experimentation in 5G and beyond Networks: State of the Art and the Way Forward

Edited by

January 2024

242 pages

ISBN978-3-7258-0046-9 (Hardback)
ISBN978-3-7258-0045-2 (PDF)

https://doi.org/10.3390/books978-3-7258-0045-2

Free download (PDF)

This book is a reprint of the Special Issue Experimentation in 5G and beyond Networks: State of the Art and the Way Forward that was published in

Chemistry & Materials Science

Engineering

Environmental & Earth Sciences

Summary

Special Issue “Experimentation in 5G and beyond Networks: State of the Art and the Way Forward” collected original contributions on experimental aspects related to 5th Generation (5G) and Beyond-5G (B5G) networks and systems.Ten high-quality papers were accepted to appear in this Special Issue, covering three main research areas: 5G testing and validation, 5G enhancements, and the use of AI/ML for B5G systems. We believe that the papers provide key updates and insights into these research areas, and thus may inspire future work aimed towards the further improvement and optimization of next-generation mobile systems.

Format

Hardback

License

Keywords

5G; testbeds; experimentation; methodology; 5th generation cellular networks (5G); remote area network; Small Unmanned Aerial Vehicles (SUAVs); Network Functions Virtualization (NFV); 3rd Generation Partnership Project (3GPP); machine learning; optimization; random access; RAN; RRH; SDR; NIB; 5G; 4G; framework; standalone; multicarrier; aggregation; 5G New Radio; QC-LDPC codes; channel encoding; encoder; low latency; 5G; NFV; neutral host; network slicing; city-wide deployments; testbed design; attack graphs; dynamic vulnerability analysis; hexagonal fuzzy number; 5G Edge security; decision-making technique; 5G security testbed; 5G; New Radio; deep learning; convolutional neural network; CSI reporting; 5G; B5G; digital health; Open RAN; private network; machine learning; UAV placement; artificial neural network (ANN); deep neural network (DNN); NOMA; cooperative communications; D2D; n/a