Explainable AI for 6G

Contributors
Foreword
Preface
Book Organization
Acknowledgments
Acronyms

I Introduction

1 Evolution of Mobile Networks
1.1 Introduction
1.2 The Rise of 5G
1.3 6G Mobile Communication Networks
1.4 6G as Envisioned Today
1.5 Key Driving Trends Towards 6G
1.6 6G Requirements and Vision
1.7 6G Development Timeline

2 Role of AI in 6G
2.1 The background of AI
2.2 History of AI

3 Background of XAI
3.1 Explainable AI
3.2 Core Terminologies
3.3 Taxonomies of Explainable AI
3.4 Explainable Reinforcement Learning (XRL)

II XAI for 6G Network Operations and Management

4 Role of XAI in 6G
4.1 Role of XAI for AI-powered 6G

5 XAI for Intelligent Radio
5.1 Requirements and Challenges
5.2 Role of XAI

6 XAI for Resource Management
6.1 Requirements and Challenges
6.2 Role of XAI

7 XAI for Edge AI
7.1 Requirements and Challenges
7.2 Role of XAI

8 XAI for Security and Privacy Trust and Security
8.1 Requirements and Challenges
8.2 Role of XAI
8.3 Requirements and Challenges
8.4 Role of XAI

9 Network Automation and Zero Touch Network and Service Management (ZSM)
9.1 Zero-Touch Network and Service Management (ZSM)
9.2 Requirements and Challenges
9.3 Role of XAI

III XAI for 6G Applications and Services

10 XAI for Multi-sensory XR Applications, Holographic Telepresence, Metaverse
10.1 Requirements and Challenges
10.2 Role of XAI

11 XAI for Smart Grid 2.0
11.1 Requirements and Challenges
11.2 Role of XAI

12 XAI for Connected Autonomous Vehicles, UAVs
12.1 Requirements and Challenges
12.2 Role of XAI

13 XAI for Industry 5.0, Collaborative Robots, Digital Twin
13.1 Requirements and Challenges
13.2 Role of XAI

14 XAI for Intelligent Health and Wearable, Body Area Networks
14.1 Requirements and Challenges
14.2 Role of XAI

IV Discussion

15 Discussion
15.1 Limitations and Challenges of XAI for 6G
15.2 Defining Research Frontiers for 6G Transparency