Artificial Intelligence for 6G
Об электронной книге
Artificial Intelligence for 6G introduces, in a step-by-step manner, AI techniques such as:
- unsupervised learning;
- supervised learning;
- reinforcement learning; and
- deep learning.
It explains how these techniques can be used for wireless communications and network systems, particularly in designing and optimizing 6G networks.
This book is at the forefront of 6G research, and will be of interest internationally, to graduate students, academics, engineers, and developers who are focused on future development of network systems and mobile communications.
Об авторе
Dr. Haesik Kim is currently with VTT Technical Research Centre of Finland. He received the Ph.D. degree from Lancaster University, UK. From 2002 to 2006, he was with Samsung Advanced Institute of Technology (SAIT) where he focused on physical layer system design and standardisation in 3G, SDR and UWB project. From 2008 to 2009, he was with NEC UK where he was involved in 4G WiMAX system design and standardisation. He made significant contributions to wireless communication and network area, including the world fastest UWB chipset development, a major contributor to WiMedia standard, dozens of patents holder deriving from his research, journal and conference papers in wireless communication area, etc. He was a vice-chair of 5G-IA steering board. He is a series editor of IEEE Communications Magazine: Design and Implementation of Devices, Circuits and Systems and also an associate technical editor of IEEE Communications Magazine. He served as a conference chair, a session chair and a TPC member of major IEEE journals and conferences. He as a coordinator, project manager and principle investigator has been involved in many EU, ESA, Finnish national projects. His current research interests include PHY and MAC layer system design, advanced coding theory, advanced MIMO, multi-carrier system, resource allocation schemes, machine-type communications, ultra-reliable low latency communications, machine learning, deep learning, etc.
