Explainable AI for Communications and Networking

Grab your copy of Explainable AI for Communications and Networking — a practical, forward-looking guide by Hatim Chergui, Melike Erol-Kantarci, and Christos Verikoukis that demystifies how explainable AI (XAI) transforms modern telecom and network design.

This book draws you in with clear explanations and real-world context: why transparency, trust, and interpretability are now essential for 5G/6G, IoT, edge computing, and software-defined networks. It explains the core XAI methods, their limitations and strengths, and how they integrate with networking workflows to improve decision-making, fault diagnosis, security, and regulatory compliance.

Designed for engineers, researchers, network operators, and tech leaders across Europe, North America, Asia-Pacific and beyond, the text balances theory and hands-on insight. Learn how model interpretability enhances performance debugging, supports explainable resource allocation, and builds stakeholder confidence in automated network actions. Chapters walk through practical case studies, evaluation metrics, and deployment strategies that make complex machine learning models understandable to non-experts and auditors alike.

If you need a single reference that bridges AI research and telecom practice, this book equips you with the concepts and tools to lead explainable, accountable network solutions. Whether you’re architecting next-generation wireless systems or shaping AI governance in communications, Explainable AI for Communications and Networking is an indispensable resource. Order now to bring clarity and trust to your network intelligence projects.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.