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 networks 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. 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 machines An 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 more Discussions of explainable neural networks and
XAI Examinations of graph neural networks, including learning
algorithms and linear and nonlinear GNNs in both classical and
quantum computing technology Perfect 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.
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