Author Description

"The book "Machine Learning for Mobile Communications" will take readers on a journey from the basic to advanced knowledge about mobile communications and machine learning. For basic levels, this book volume discusses a wide range of mobile communications topics from the system level such as system design, optimization to the user level such as power control, resource allocation. It also reviews state-of-art Machine Learning which is one of the biggest emerging trends for both academic and industrials. For the advanced level, this book provides knowledge about how to utilize Machine Learning to design and solve the problems of future mobile communications. It discusses solutions for long-term problems such as resource allocation, security, power control, and spectral efficiency. This book brings together some of the top mobile communication and Machine Learning experts throughout the world who contribute their knowledge and experience regarding system design and optimization. This book: Discusses the 5G new radio system design, and architecture as specified in 3GPP documents. Highlights the challenges including security and privacy, energy, and spectrum efficiency from the perspective of 5G new radio systems. Identifies both theoretical and practical problems that can occur in mobile communication systems. Covers machine learning techniques such as autoencoder, and Q-learning in a comprehensive manner. Explores how to apply machine learning techniques to mobile systems to solve modern problems. This book is for senior undergraduate and graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, and computer engineering"--