Artificial Intelligence and Quantum Computing for Advanced Wireless Networks 1st edition by Savo Glisic 1119790310 9781119790310

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ISBN-10 :  1119790310 

ISBN-13 :  9781119790310

Author: Savo G. Glisic 

Increasingly dense and flexible wireless networks require the use of artificial intelligence (AI) for planning network deployment, optimization, and dynamic control. Machine learning algorithms are now often used to predict traffic and network state in order to reserve resources for smooth communication with high reliability and low latency.

In Artificial Intelligence and Quantum Computing for Advanced Wireless Networks, the authors deliver a practical and timely review of AI-based learning algorithms, with several case studies in both Python and R. The book discusses the game-theory-based learning algorithms used in decision making, along with various specific applications in wireless networks, like channel, network state, and traffic prediction. Additional chapters include Fundamentals of ML, Artificial Neural Networks (NN), Explainable and Graph NN, Learning Equilibria and Games, AI Algorithms in Networks, Fundamentals of Quantum Communications, Quantum Channel, Information Theory and Error Correction, Quantum Optimization Theory, and Quantum Internet, to name a few.

Artificial Intelligence and Quantum Computing for Advanced Wireless Networks 1st Table of contents:

Part I: Artificial Intelligence
1 Introduction
1.1 Motivation
1.2 Book Structure
References
2 Machine Learning Algorithms
2.1 Fundamentals
2.2 ML Algorithm Analysis
References
3 Artificial Neural Networks
3.1 Multi‐layer Feedforward Neural Networks
3.2 FIR Architecture
3.3 Time Series Prediction
3.4 Recurrent Neural Networks
3.5 Cellular Neural Networks (CeNN)
3.6 Convolutional Neural Network (CoNN)
References
4 Explainable Neural Networks
4.1 Explainability Methods
4.2 Relevance Propagation in ANN
4.3 Rule Extraction from LSTM Networks
4.4 Accuracy and Interpretability
References
5 Graph Neural Networks
5.1 Concept of Graph Neural Network (GNN)
5.2 Categorization and Modeling of GNN
5.3 Complexity of NN
Appendix 5.A Notes on Graph Laplacian
Appendix 5.B Graph Fourier Transform
References
6 Learning Equilibria and Games
6.1 Learning in Games
6.2 Online Learning of Nash Equilibria in Congestion Games
6.3 Minority Games
6.4 Nash Q‐Learning
6.5 Routing Games
6.6 Routing with Edge Priorities
References
7 AI Algorithms in Networks
7.1 Review of AI‐Based Algorithms in Networks
7.2 ML for Caching in Small Cell Networks
7.3 Q‐Learning‐Based Joint Channel and Power Level Selection in Heterogeneous Cellular Networks
7.4 ML for Self‐Organizing Cellular Networks
7.5 RL‐Based Caching
7.6 Big Data Analytics in Wireless Networks
7.7 Graph Neural Networks
7.8 DRL for Multioperator Network Slicing
7.9 Deep Q‐Learning for Latency‐Limited Network Virtualization
7.10 Multi‐Armed Bandit Estimator (MBE)
7.11 Network Representation Learning
References
Part II: Quantum Computing
8 Fundamentals of Quantum Communications
8.1 Introduction
8.2 Quantum Gates and Quantum Computing
8.3 Quantum Fourier Transform (QFT)
References
9 Quantum Channel Information Theory
9.1 Communication Over a Channel
9.2 Quantum Information Theory
9.3 Channel Description
9.4 Channel Classical Capacities
9.5 Channel Quantum Capacity
9.6 Quantum Channel Examples
References
10 Quantum Error Correction
10.1 Stabilizer Codes
10.2 Surface Code
10.3 Fault‐Tolerant Gates
10.4 Theoretical Framework
10.A Binary Fields and Discrete Vector Spaces
10.B Some Noise Physics
References
11 Quantum Search Algorithms
11.1 Quantum Search Algorithms
11.2 Physics of Quantum Algorithms
References
12 Quantum Machine Learning
12.1 QML Algorithms
12.2 QNN Preliminaries
12.3 Quantum Classifiers with ML: Near‐Term Solutions
12.4 Gradients of Parameterized Quantum Gates
12.5 Classification with QNNs
12.6 Quantum Decision Tree Classifier
Appendix 12.7 Matrix Exponential
References
13 QC Optimization
13.1 Hybrid Quantum‐Classical Optimization Algorithms
13.2 Convex Optimization in Quantum Information Theory
13.3 Quantum Algorithms for Combinatorial Optimization Problems
13.4 QC for Linear Systems of Equations
13.5 Quantum Circuit
13.6 Quantum Algorithm for Systems of Nonlinear Differential Equations
References
14 Quantum Decision Theory
14.1 Potential Enablers for Qc
14.2 Quantum Game Theory (QGT)
14.3 Quantum Decision Theory (QDT)
14.4 Predictions in QDT
References
15 Quantum Computing in Wireless Networks
15.1 Quantum Satellite Networks
15.2 QC Routing for Social Overlay Networks
15.3 QKD Networks
References
16 Quantum Network on Graph
16.1 Optimal Routing in Quantum Networks
16.2 Quantum Network on Symmetric Graph
16.3 QWs
16.4 Multidimensional QWs
References
17 Quantum Internet
17.1 System Model
17.2 Quantum Network Protocol Stack

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