Zeeshan Kaleem – författare

This book provides a comprehensive overview of the potential use cases and intelligent technologies, UAV layered architectures, research findings, experimental results, and standardization for intelligent UAV communications for public safety networks.

This book provides a comprehensive overview of the potential use cases and intelligent technologies, UAV layered architectures, research findings, experimental results, and standardization for intelligent UAV communications for public safety networks. This book will cover the conventional non-intelligent and intelligent solutions specifically targeting UAV communications for public safety networks. Moreover, reconfigurable intelligent surface (RIS) has recently attracted researchers and academician attention because its ability improves the propagation environment and enhances communication quality by intelligently reflecting the received signals. Leveraging intelligence into RIS-assisted UAV communications will meet the requirements of the intelligent, green, and sustainable 5G and beyond cellular networks, which makes it a potential candidate to overcome the inherent drawbacks of legacy wireless systems.The topics covered in this book will be of interest to both the professionals and students. 3D UAV placements schemes, trajectory design, interference management schemes, reinforcement learning solutions for more intelligent and trained solutions, joint UAV trajectory and RIS's passive beamforming design, and various other related topics of readers' interest are presented in detail.

This book thoroughly covers the prospective use cases, intelligent technologies, layered architectures for RIS-assisted UAV communications, research findings, experimental discoveries, and standardizations . The standard non-intelligent and intelligent approaches especially aimed for RIS-assisted UAV communications will be covered in this book. Additionally, researchers and academicians have lately become interested in improving beamforming/reflection for RIS-assisted UAV networks because of its capacity to boost communication coverage, quality, and privacy by dynamically reflecting the incoming signal. The ability to incorporate intelligence via machine learning techniques adopted in the RIS-assisted UAV communications satisfies the criteria for intelligent, environmentally friendly, and self-sustaining 6G cellular networks, making it a potential candidate to address the limitations of existing wireless technologies. Students and professionals alike will find the issues discussed in this book to be interesting. Security, a massive, ultra-reliable, and low-latency communication systems, reinforcement learning and/or deep learning methods for further intelligent and trained strategies, RIS’s beamforming and order of power scaling, as well as a number of other relevant issues of readers’ concern are described in detail.