[eBook Code] Artificial Intelligence and Quantum Computing for Advanced Wireless Networks (eBook Code, 1st)

Preface, xiii

Part I Artificial Intelligence, 1

1 Introduction, 3

1.1 Motivation, 3

1.2 Book Structure, 5

2 Machine Learning Algorithms, 17

2.1 Fundamentals, 17

2.2 ML Algorithm Analysis, 37

3 Artificial Neural Networks, 55

3.1 Multi-layer Feedforward Neural Networks, 55

3.2 FIR Architecture, 60

3.3 Time Series Prediction, 68

3.4 Recurrent Neural Networks, 69

3.5 Cellular Neural Networks (CeNN), 81

3.6 Convolutional Neural Network (CoNN), 84

4 Explainable Neural Networks, 97

4.1 Explainability Methods, 99

4.2 Relevance Propagation in ANN, 103

4.3 Rule Extraction from LSTM Networks, 110

4.4 Accuracy and Interpretability, 112

5 Graph Neural Networks, 135

5.1 Concept of Graph Neural Network (GNN), 135

5.2 Categorization and Modeling of GNN, 144

5.3 Complexity of NN, 156

6 Learning Equilibria and Games, 179

6.1 Learning in Games, 179

6.2 Online Learning of Nash Equilibria in Congestion Games, 196

6.3 Minority Games, 202

6.4 Nash Q-Learning, 204

6.5 Routing Games, 211

6.6 Routing with Edge Priorities, 220

7 AI Algorithms in Networks, 227

7.1 Review of AI-Based Algorithms in Networks, 227

7.2 ML for Caching in Small Cell Networks, 237

7.3 Q-Learning-Based Joint Channel and Power Level Selection in Heterogeneous Cellular Networks, 243

7.4 ML for Self-Organizing Cellular Networks, 252

7.5 RL-Based Caching, 267

7.6 Big Data Analytics in Wireless Networks, 274

7.7 Graph Neural Networks, 279

7.8 DRL for Multioperator Network Slicing, 291

7.9 Deep Q-Learning for Latency-Limited Network Virtualization, 302

7.10 Multi-Armed Bandit Estimator (MBE), 317

7.11 Network Representation Learning, 327

Part II Quantum Computing, 361

8 Fundamentals of Quantum Communications, 363

8.1 Introduction, 363

8.2 Quantum Gates and Quantum Computing, 372

8.3 Quantum Fourier Transform (QFT), 386

9 Quantum Channel Information Theory, 397

9.1 Communication Over a Channel, 398

9.2 Quantum Information Theory, 401

9.3 Channel Description, 407

9.4 Channel Classical Capacities, 414

9.5 Channel Quantum Capacity, 431

9.6 Quantum Channel Examples, 437

10 Quantum Error Correction, 451

10.1 Stabilizer Codes, 458

10.2 Surface Code, 465

10.3 Fault-Tolerant Gates, 471

10.4 Theoretical Framework, 474

11 Quantum Search Algorithms, 499

11.1 Quantum Search Algorithms, 499

11.2 Physics of Quantum Algorithms, 510

12 Quantum Machine Learning, 543

12.1 QML Algorithms, 543

12.2 QNN Preliminaries, 547

12.3 Quantum Classifiers with ML: Near-Term Solutions, 550

12.4 Gradients of Parameterized Quantum Gates, 560

12.5 Classification with QNNs, 568

12.6 Quantum Decision Tree Classifier, 575

13 QC Optimization, 593

13.1 Hybrid Quantum-Classical Optimization Algorithms, 593

13.2 Convex Optimization in Quantum Information Theory, 601

13.3 Quantum Algorithms for Combinatorial Optimization Problems, 609

13.4 QC for Linear Systems of Equations, 614

13.5 Quantum Circuit, 625

13.6 Quantum Algorithm for Systems of Nonlinear Differential Equations, 628

14 Quantum Decision Theory, 637

14.1 Potential Enablers for Qc, 637

14.2 Quantum Game Theory (QGT), 641

14.3 Quantum Decision Theory (QDT), 665

14.4 Predictions in QDT, 676

15 Quantum Computing in Wireless Networks, 693

15.1 Quantum Satellite Networks, 693

15.2 QC Routing for Social Overlay Networks, 706

15.3 QKD Networks, 713

16 Quantum Network on Graph, 733

16.1 Optimal Routing in Quantum Networks, 733

16.2 Quantum Network on Symmetric Graph, 744

16.3 QWs, 747

16.4 Multidimensional QWs, 753

17 Quantum Internet, 773

17.1 System Model, 775

17.2 Quantum Network Protocol Stack, 789

References, 814

Index, 821