Artificial intelligence for 6G / Haesik Kim.

Format:

Book

Author/Creator:

Kim, Haesik, author.

Language:

English

Subjects (All):

Wireless communication systems--Design and construction.

Wireless communication systems.

Wireless communication systems--Economic aspects.

Physical Description:

1 online resource (534 pages)

Place of Publication:

Cham, Switzerland : Springer International Publishing, [2022]

Summary:

This textbook introduces Artificial Intelligence (AI) techniques for wireless communications and networks, helping readers to find solutions for communications and network problems using AI. Artificial Intelligence for 6G introduces, in a step-by-step manner, AI techniques such as: unsupervised learning; supervised learning; reinforcement learning; and deep learning. It explains how these techniques can be used for wireless communications and network systems, particularly in designing and optimizing 6G networks. This book is at the forefront of 6G research, and will be of interest internationally, to graduate students, academics, engineers, and developers who are focused on future development of network systems and mobile communications.

Contents:

Intro

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

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

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

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

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

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

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

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

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

Index.

Notes:

Description based on print version record.

Other Format:

Print version: Kim, Haesik Artificial Intelligence For 6G

ISBN:

9783030950415