Explainable AI for Communications and Networking

Responsible and Explainable AI for Communications and Networking gives a tour into the realm of Explainable Artificial Intelligence (XAI) and its impact on transparent and autonomous communication networks. It equips readers from diverse backgrounds in communications and networking with powerful XAI tools to demystify AI systems in a clear and concise manner. Additionally, the book provides detailed insights into XAI deployment scenarios and architectures in future B5G/6G systems. Use cases and real-world applications demonstrate the transformative potential of XAI in enhancing network performance optimization, fault management, and communication systems design, providing valuable insights from industry experts. The book explains the regulatory, ethical, and legal implications of XAI in telecommunications, ensuring responsible deployment and mitigating biases and unintended consequences. Finally, it looks into the future, exploring emerging trends and directions in XAI. With this book the reader will learn:

• Different architectures and design options to integrate XAI in B5G/6G networks
• How to use XAI for network performance optimization and fault management
• How to devise algorithms that bridge the AI performance-explainability trade-off, to ease their practical adoption in live networks
• Different use-cases of XAI in key application areas related to communications and networking
• The regulatory, ethical and legal implications of XAI in telecommunication networks.

• Includes XAI deployment architectures (such as on top of O-RAN)
• Use-cases such as QoE optimization, SLA assurance, traffic steering, multi-vendor slice
• Gives practical examples (for example, performing root cause analysis of network faults)
• Includes implementation guidelines (XAI libraries/implementation tools) tailored to the communications and networking context.