Reprint
Optimization and Communication in UAV Networks
Edited by
October 2020
264 pages
- ISBN978-3-03943-310-0 (Hardback)
- ISBN978-3-03943-311-7 (PDF)
This book is a reprint of the Special Issue Optimization and Communication in UAV Networks that was published in
Chemistry & Materials Science
Engineering
Environmental & Earth Sciences
Summary
UAVs are becoming a reality and attract increasing attention. They can be remotely controlled or completely autonomous and be used alone or as a fleet and in a large set of applications. They are constrained by hardware since they cannot be too heavy and rely on batteries. Their use still raises a large set of exciting new challenges in terms of trajectory optimization and positioning when they are used alone or in cooperation, and communication when they evolve in swarm, to name but a few examples. This book presents some new original contributions regarding UAV or UAV swarm optimization and communication aspects.
Format
- Hardback
License and Copyright
© 2020 by the authors; CC BY-NC-ND license
Keywords
direction-of-arrival estimation; unmanned aerial vehicles; UAV swarm; aperiodic arrays; MUSIC; Cramer–Rao bound; stochastic system; UAV swarm; configuration control; multiplicative noises; dynamic model; stochastic robustness analysis and design; wireless sensor networks; unmanned aerial vehicle; mission completion time; trajectory planning; UAV secure communication; secrecy rate maximization; jamming; trajectory design; power control; unmanned aerial vehicles; trajectory planning; sensors; data collection utility; GPS measurement; UAV; 3D models; measurement precision; unmanned aerial vehicle (UAV); cooperative communication; topology structure; complex field network coding (CFNC); edge computing; internet of things; mobile robots; resource allocation; control co-design; data offloading; UAV-enabled computing; resource-based pricing; risk-awareness; multi-access edge computing systems; UAV; UAV fleet; UAV swarm; energy consumption; self-organization; algorithms; optimization; UAV replacement; wireless sensor networks; multiple unmanned aerial vehicles; mobile nodes; data collection; collision-free; unmanned aerial vehicle; synchronized multi-agent formation; decentralized sliding mode control; UAV; drones; wireless; self-organization; optimization; swarm; communication; algorithms