TY - JOUR
T1 - Exploring UAV Networking from the Terrain Information Completeness Perspective
T2 - A Tutorial
AU - Lou, Zhengying
AU - Wang, Ruibo
AU - Belmekki, Baha Eddine Youcef
AU - Kishk, Mustafa A.
AU - Alouini, Mohamed Slim
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2024
Y1 - 2024
N2 - Terrain information is a crucial factor affecting the performance of unmanned aerial vehicle (UAV) networks. As a tutorial, this article provides a unique perspective on the completeness of terrain information, summarizing and enhancing the research on terrain-based UAV deployment. In the presence of complete terrain information, two highly discussed topics are UAV-aided map construction and dynamic trajectory design based on maps. We propose a case study illustrating the mutually reinforcing relationship between them. When terrain information is incomplete, and only terrain-related feature parameters are available, we discuss how existing models map terrain features to blockage probabilities. By introducing the application of this model with stochastic geometry, a case study is proposed to analyze the accuracy of the model. When no terrain information is available, UAVs gather terrain information during the real-time networking process and determine the next position by collected information. This real-time search method is currently limited to relay communication. In the case study, we extend it to a multi-user scenario and summarize three trade-offs of the method. Finally, we conduct a qualitative analysis to assess the impact of three factors that have been overlooked in terrain-based UAV deployment.
AB - Terrain information is a crucial factor affecting the performance of unmanned aerial vehicle (UAV) networks. As a tutorial, this article provides a unique perspective on the completeness of terrain information, summarizing and enhancing the research on terrain-based UAV deployment. In the presence of complete terrain information, two highly discussed topics are UAV-aided map construction and dynamic trajectory design based on maps. We propose a case study illustrating the mutually reinforcing relationship between them. When terrain information is incomplete, and only terrain-related feature parameters are available, we discuss how existing models map terrain features to blockage probabilities. By introducing the application of this model with stochastic geometry, a case study is proposed to analyze the accuracy of the model. When no terrain information is available, UAVs gather terrain information during the real-time networking process and determine the next position by collected information. This real-time search method is currently limited to relay communication. In the case study, we extend it to a multi-user scenario and summarize three trade-offs of the method. Finally, we conduct a qualitative analysis to assess the impact of three factors that have been overlooked in terrain-based UAV deployment.
KW - blockage verification
KW - network performance
KW - terrain information
KW - UAV deployment
UR - http://www.scopus.com/inward/record.url?scp=85190167176&partnerID=8YFLogxK
U2 - 10.1109/OJVT.2024.3386064
DO - 10.1109/OJVT.2024.3386064
M3 - Article
AN - SCOPUS:85190167176
SN - 2644-1330
VL - 5
SP - 620
EP - 631
JO - IEEE Open Journal of Vehicular Technology
JF - IEEE Open Journal of Vehicular Technology
ER -