Artificial Intelligence and Quantum Computing for Advanced Wireless Networks

Inbunden, Engelska, 2022

1 681 kr

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Beskrivning

ARTIFICIAL INTELLIGENCE AND QUANTUM COMPUTING FOR ADVANCED WIRELESS NETWORKS A comprehensive presentation of the implementation of artificial intelligence and quantum computing technology in large-scale communication networksIncreasingly 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.The authors offer readers an intuitive and accessible path from basic topics on machine learning through advanced concepts and techniques in quantum networks. Readers will benefit from: A thorough introduction to the fundamentals of machine learning algorithms, including linear and logistic regression, decision trees, random forests, bagging, boosting, and support vector machinesAn exploration of artificial neural networks, including multilayer neural networks, training and backpropagation, FIR architecture spatial-temporal representations, quantum ML, quantum information theory, fundamentals of quantum internet, and moreDiscussions of explainable neural networks and XAIExaminations of graph neural networks, including learning algorithms and linear and nonlinear GNNs in both classical and quantum computing technologyPerfect for network engineers, researchers, and graduate and masters students in computer science and electrical engineering, Artificial Intelligence and Quantum Computing for Advanced Wireless Networks is also an indispensable resource for IT support staff, along with policymakers and regulators who work in technology.

Produktinformation

Utgivningsdatum:2022-03-17
Mått:178 x 254 x 52 mm
Vikt:1 758 g
Format:Inbunden
Språk:Engelska
Antal sidor:864
Förlag:John Wiley & Sons Inc
ISBN:9781119790297

Utforska kategorier

Nätverk och kommunikation inom Data och IT

Mer om författaren

Savo G. Glisic is Research Professor at Worcester Polytechnic Institute, Massachusetts, USA. His research interests include network optimization theory, network topology control and graph theory, cognitive networks, game theory, artificial intelligence, and quantum computing technology.Beatriz Lorenzo is Assistant Professor in the Department of Electrical and Computer Engineering at the University of Massachusetts Amherst, USA. Her research interests include the areas of communication networks, wireless networks, and mobile computing.

Innehållsförteckning

Preface, xiiiPart I Artificial Intelligence, 11 Introduction, 31.1 Motivation, 31.2 Book Structure, 52 Machine Learning Algorithms, 172.1 Fundamentals, 172.2 ML Algorithm Analysis, 373 Artificial Neural Networks, 553.1 Multi-layer Feedforward Neural Networks, 553.2 FIR Architecture, 603.3 Time Series Prediction, 683.4 Recurrent Neural Networks, 693.5 Cellular Neural Networks (CeNN), 813.6 Convolutional Neural Network (CoNN), 844 Explainable Neural Networks, 974.1 Explainability Methods, 994.2 Relevance Propagation in ANN, 1034.3 Rule Extraction from LSTM Networks, 1104.4 Accuracy and Interpretability, 1125 Graph Neural Networks, 1355.1 Concept of Graph Neural Network (GNN), 1355.2 Categorization and Modeling of GNN, 1445.3 Complexity of NN, 1566 Learning Equilibria and Games, 1796.1 Learning in Games, 1796.2 Online Learning of Nash Equilibria in Congestion Games, 1966.3 Minority Games, 2026.4 Nash Q-Learning, 2046.5 Routing Games, 2116.6 Routing with Edge Priorities, 2207 AI Algorithms in Networks, 2277.1 Review of AI-Based Algorithms in Networks, 2277.2 ML for Caching in Small Cell Networks, 2377.3 Q-Learning-Based Joint Channel and Power Level Selection in Heterogeneous Cellular Networks, 2437.4 ML for Self-Organizing Cellular Networks, 2527.5 RL-Based Caching, 2677.6 Big Data Analytics in Wireless Networks, 2747.7 Graph Neural Networks, 2797.8 DRL for Multioperator Network Slicing, 2917.9 Deep Q-Learning for Latency-Limited Network Virtualization, 3027.10 Multi-Armed Bandit Estimator (MBE), 3177.11 Network Representation Learning, 327Part II Quantum Computing, 3618 Fundamentals of Quantum Communications, 3638.1 Introduction, 3638.2 Quantum Gates and Quantum Computing, 3728.3 Quantum Fourier Transform (QFT), 3869 Quantum Channel Information Theory, 3979.1 Communication Over a Channel, 3989.2 Quantum Information Theory, 4019.3 Channel Description, 4079.4 Channel Classical Capacities, 4149.5 Channel Quantum Capacity, 4319.6 Quantum Channel Examples, 43710 Quantum Error Correction, 45110.1 Stabilizer Codes, 45810.2 Surface Code, 46510.3 Fault-Tolerant Gates, 47110.4 Theoretical Framework, 47411 Quantum Search Algorithms, 49911.1 Quantum Search Algorithms, 49911.2 Physics of Quantum Algorithms, 51012 Quantum Machine Learning, 54312.1 QML Algorithms, 54312.2 QNN Preliminaries, 54712.3 Quantum Classifiers with ML: Near-Term Solutions, 55012.4 Gradients of Parameterized Quantum Gates, 56012.5 Classification with QNNs, 56812.6 Quantum Decision Tree Classifier, 57513 QC Optimization, 59313.1 Hybrid Quantum-Classical Optimization Algorithms, 59313.2 Convex Optimization in Quantum Information Theory, 60113.3 Quantum Algorithms for Combinatorial Optimization Problems, 60913.4 QC for Linear Systems of Equations, 61413.5 Quantum Circuit, 62513.6 Quantum Algorithm for Systems of Nonlinear Differential Equations, 62814 Quantum Decision Theory, 63714.1 Potential Enablers for Qc, 63714.2 Quantum Game Theory (QGT), 64114.3 Quantum Decision Theory (QDT), 66514.4 Predictions in QDT, 67615 Quantum Computing in Wireless Networks, 69315.1 Quantum Satellite Networks, 69315.2 QC Routing for Social Overlay Networks, 70615.3 QKD Networks, 71316 Quantum Network on Graph, 73316.1 Optimal Routing in Quantum Networks, 73316.2 Quantum Network on Symmetric Graph, 74416.3 QWs, 74716.4 Multidimensional QWs, 75317 Quantum Internet, 77317.1 System Model, 77517.2 Quantum Network Protocol Stack, 789References, 814Index, 821