Artificial Intelligence for 6G (2022) [Kim] [9783030950408]

✍ Scribed by Kim

• Year: 2022
• Tongue: English
• Leaves: 534
• Category: Library

✦ Synopsis

Artificial Intelligence for 6G (2022) [Kim] [9783030950408]

✦ Table of Contents

Preface
Contents
Abbreviations
Part I Artificial Intelligence Techniques
1 Historical Sketch of Artificial Intelligence
1.1 Introduction to Artificial Intelligence
1.2 History of Artificial Intelligence
References
2 Artificial Intelligence Ecosystem, Techniques, and Use Cases
2.1 Artificial Intelligence Ecosystem
2.2 Hardware and Software of Artificial Intelligence
2.3 Artificial Intelligence Techniques and Selection
2.4 Artificial Intelligence Workflow and Use Cases
References
3 Unsupervised Learning
3.1 Types and Performance Metrics of Unsupervised Learning
3.2 Clustering Algorithms
3.2.1 Hierarchical Clustering
3.2.2 Partitional Clustering
3.3 Association Rule Mining
3.4 Dimensionality Reduction
3.5 Problems
References
4 Supervised Learning
4.1 Supervised Learning Workflow, Metrics, and Ensemble Methods
4.2 Classification of Supervised Learning
4.2.1 Decision Tree
4.2.2 K-Nearest Neighbours
4.2.3 Support Vector Machine
4.3 Regression of Supervised Learning
4.3.1 Linear Regression
4.3.2 Gradient Descent Algorithms
4.3.3 Logistic Regression
4.4 Problems
References
5 Reinforcement Learning
5.1 Introduction to Reinforcement Learning and Markov Decision Process
5.2 Model-Based Approaches
5.2.1 Policy Iteration
5.2.2 Value Iteration
5.3 Model-Free Approaches
5.3.1 Monte Carlo Methods
5.3.2 Temporal difference learning methods
5.4 Problems
References
6 Deep Learning
6.1 Introduction to Deep Learning
6.2 Deep Neural Network
6.3 Convolutional Neural Network
6.4 Recurrent Neural Network
6.5 Problems
References
Part II AI-Enabled Communications and Networks Techniques for 6G
7 6G Wireless Communications and Networks Systems
7.1 6G Wireless Communications and Networks
7.1.1 6G Use Cases and Requirements
7.1.2 6G Timeline, Technical Requirements, and Technical Challenges
7.1.3 6G Key Enabling Techniques
7.2 AI-Enabled 6G Wireless Communications and Networks
7.2.1 AI and ML Contributions to Physical Layers
7.2.2 AI and ML Contribution to Data Link and Network Layers and Open Research Challenges
7.3 Problems
References
8 AI-Enabled Physical Layer
8.1 Design Approaches of AI-Enabled Physical Layer
8.2 End-To-End Physical Layer Redesign with Autoencoder
8.3 Wireless Channel Models
8.4 Signal Detection and Modulation
8.5 Channel Estimation
8.6 Error Control Coding
8.7 MIMO
8.8 Problems
References
9 AI-Enabled Data Link Layer
9.1 Design Approaches of AI-Enabled Data Link Layer
9.2 Radio Resource Allocation and Scheduling
9.2.1 Resource Allocation Problems in Wireless Networks and Convex Optimization
9.2.2 Resource Allocation Models and Performance Measure
9.2.3 Utility Functions and Fairness of Resource Allocation
9.2.4 Resource Allocation Using AI Techniques
9.3 Handover Using AI Techniques
9.4 Problems
References
10 AI-Enabled Network Layer
10.1 Design Approaches of AI-Enabled Network Layer
10.2 Cellular Systems and Networking
10.2.1 Evolution of Cellular Networks
10.2.2 Concept of Cellular Systems
10.2.3 Cell Planning
10.3 Network Traffic Prediction
10.3.1 Classic Network Traffic Prediction
10.3.2 AI-Enabled Network Traffic Prediction
10.4 Problems
References
Index