Explainable AI for Communications and Networking: Toward Responsible Automation

by Hatim Chergui PhD (Editor), Melike Erol-Kantarci Phd (Editor), Christos Verikoukis PhD (Editor)

Overview

Explainable AI for Communications and Networking: Toward Responsible Automation gives a tour into the realm of Explainable Artificial Intelligence (XAI) and its impact on transparent and autonomous communication networks. The book equips readers from diverse backgrounds in communications and networking with a variety of XAI tools, metrics and frameworks to demystify AI systems through graphical taxonomies and mathematical formulations, which are further enriched with code snippets. The book also examines XAI implementation in wireless communications, network management, generative AI for telecom and cybersecurity, before presenting practical use-cases emanating from an industry perspective. Finally, the regulatory, ethical, and legal implications of XAI in telecommunications are reviewed, before concluding with key challenges and takeaways. - Includes XAI graphical taxonomies, metrics, formulations and code snippets. - Provides practical examples and use-cases from a telecom industry perspective. - Covers implementation guidelines (XAI libraries/implementation tools) tailored to a communications and networking context. - Highlights the application of XAI in wireless communications, network management, generative AI for telecom and cybersecurity. - Presents a thorough synthesis of the regulatory and ethical implications of XAI worldwide.

Product Details

ISBN-13:	9780443291364
Publisher:	Elsevier Science & Technology Books
Publication date:	04/08/2025
Sold by:	Barnes & Noble
Format:	eBook
Pages:	225
File size:	31 MB
Note:	This product may take a few minutes to download.

About the Author

Hatim Chergui (IEEE SM'22) received the Ph.D. degree (summa cum laude) in electrical engineering and telecommunications from IMT-Atlantique (Télécom-Bretagne), Brest, France. He is a Senior Researcher at i2CAT Foundation, Barcelona, Spain. He was the project manager of the H2020 MonB5G European project and a researcher at CTTC, Spain. He served as a RAN expert at both INWI and Huawei Technologies, Morocco. He was the recipient of the IEEE ComSoc CSIM 2021 Best Journal Paper Award and the IEEE ICC 2020 Best Paper Award. He is an Associate Editor of IEEE Networking Letters.
Dr. Melike Erol-Kantarci is Canada Research Chair (Tier 2) in AI-Enabled Next-Generation Wireless Networks and Full Professor at the School of Electrical Engineering and Computer Science at the University of Ottawa, ON, Canada. She is also Chief Cloud RAN AI\ML Data Scientist at Ericsson. She is the founding director of the Networked Systems and Communications Research (NETCORE) laboratory. She is a Faculty Affiliate at the Vector Institute and the Institute for Science, Society and Policy. She is also a courtesy faculty at the Department of Electrical and Computer Engineering at Clarkson University, Potsdam, NY.
Prof. Christos Verikoukis got his PhD from the Signal Theory and Communications Department of the Technical University of Catalonia (UPC), Barcelona, in 2000, in Broadband Indoor Wireless Communications. He is an Associate Professor with the University of Patras, CEI Department. He has published 147 journal papers, more than 220 conference papers and 18 chapters in different books. He is also co-author of 4 Books and he filled 4 patents. His publications received more than 7500 citations.

Table of Contents

1. AI-Driven Network Automation2. Explainable AI Overview3. XAI Metrics and Frameworks4. XAI for Wireless Communications5. Neuro-Symbolic XAI for Communications6. XAI for Network Management7. Responsible Generative AI for Telecom8. Explainable AI for Cybersecurity Decision: Challenges and Opportunities9. Explainable AI for Telecom Use-Cases10. XAI: Regulatory and Ethical Aspects11. Future Directions and Challenges12. Conclusions: A Human-Centric Perspective