With the advent of Big Data, conventional communication networks are often limited in their inability to handle complex and voluminous data and information as far as effective processing, transmission, and reception are concerned. This book discusses the evolution of computational intelligence techniques in handling intelligent communication networks.

• Provides a detailed theoretical foundation of machine learning and computational intelligence algorithms
• Highlights the state of art machine learning-based solutions for communication networks
• Presents video demonstrations and code snippets on each chapter for easy understanding of the concepts
• Discusses applications including resource allocation, spectrum management, channel estimation, and physical layer of wireless networks
• Demonstrates applications of machine learning techniques for optical networks

The text is primarily intended for senior undergraduate and graduate students and academic researchers in fields of electrical engineering, electronics and communication engineering, and computer engineering.

With the advent of Big Data, conventional communication networks are often limited in their inability to handle complex and voluminous data and information as far as effective processing, transmission, and reception are concerned. This book discusses the evolution of computational intelligence techniques in handling intelligent communication networks.

• Provides a detailed theoretical foundation of machine learning and computational intelligence algorithms
• Highlights the state of art machine learning-based solutions for communication networks
• Presents video demonstrations and code snippets on each chapter for easy understanding of the concepts
• Discusses applications including resource allocation, spectrum management, channel estimation, and physical layer of wireless networks
• Demonstrates applications of machine learning techniques for optical networks

The text is primarily intended for senior undergraduate and graduate students and academic researchers in fields of electrical engineering, electronics and communication engineering, and computer engineering.

With the advent of Big Data, conventional communication networks are often limited in their inability to handle complex and voluminous data and information as far as effective processing, transmission, and reception are concerned. This book discusses the evolution of computational intelligence techniques in handling intelligent communication networks.

• Provides a detailed theoretical foundation of machine learning and computational intelligence algorithms
• Highlights the state of art machine learning-based solutions for communication networks
• Presents video demonstrations and code snippets on each chapter for easy understanding of the concepts
• Discusses applications including resource allocation, spectrum management, channel estimation, and physical layer of wireless networks
• Demonstrates applications of machine learning techniques for optical networks

The text is primarily intended for senior undergraduate and graduate students and academic researchers in fields of electrical engineering, electronics and communication engineering, and computer engineering.