Machine Learning For Wireless Communication
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Deep Learning in Wireless Communications
The book offers a focused examination of deep learning-based wireless communication systems and their applications. While both principles and engineering practice are explored, greater emphasis is placed on the latter. The book offers an in-depth exploration of major topics such as cognitive spectrum intelligence, learning resource allocation optimization, transmission intelligence, learning traffic and mobility prediction, and security in wireless communication. Notably, the book provides a comprehensive and systematic treatment of practical issues related to intelligent wireless communication, making it particularly useful for those seeking to learn about practical solutions in AI-based wireless resource management. This book is a valuable resource for researchers, engineers, and graduate students in the fields of wireless communication, telecommunications, and related areas.
Machine Learning for Wireless Communication
Machine Learning for Wireless Communication: Principles and Applications Edited by Dr. Sanjay Agal Unlock the future of connectivity where algorithms power intelligent communication systems. Machine Learning for Wireless Communication: Principles and Applications is your essential guide to the transformative synergy between machine learning and next-generation wireless technologies. Whether you're a researcher, student, or industry professional, this comprehensive volume bridges the gap between theory and practical application. Covering foundational concepts-from supervised and unsupervised learning to deep learning and reinforcement learning-it progresses into real-world applications such as 5G/6G optimization, IoT integration, edge computing, and network security. With clear explanations, illustrative case studies, and insights from seasoned educators and engineers, this book goes beyond technical depth to offer a strategic vision of how data-driven intelligence is reshaping wireless networks. Step into a world where machines not only learn but anticipate, adapt, and revolutionize how we connect.
Applications of Machine Learning in Wireless Communications
Author: Ruisi He
language: en
Publisher: Institution of Engineering and Technology
Release Date: 2019-06-20
Machine learning explores the study and development of algorithms that can learn from and make predictions and decisions based on data. Applications of machine learning in wireless communications have been receiving a lot of attention, especially in the era of big data and IoT, where data mining and data analysis technologies are effective approaches to solving wireless system evaluation and design issues.