Cloud Shape and Attenuation Based UAV Trajectory Optimization for FSO Communication

Unmanned aerial vehicle (UAV) enabled wireless network systems are promising technology for future 6G communications. In this article, UAV trajectory optimization techniques for free space optics (FSO) communication is studied, especially considering the atmospheric effects of clouds on FSO links. I...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on vehicular technology 2024-07, Vol.73 (7), p.9911-9926
Main Authors: Ko, Da-Eun, Song, Sooeun, Choi, Minsu, Chung, Jong-Moon
Format: Article
Language:English
Subjects:
Algorithms
Atmospheric effects
Attenuation
Autonomous aerial vehicles
cloud
Cloud computing
Clouds
Communication
Communications systems
Convex functions
convex optimization
Convexity
Energy efficiency
Free space optics
FSO
Optimization techniques
Shape
trajectory
Trajectory optimization
UAV
Unmanned aerial vehicles
Wireless communications
Wireless networks
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Unmanned aerial vehicle (UAV) enabled wireless network systems are promising technology for future 6G communications. In this article, UAV trajectory optimization techniques for free space optics (FSO) communication is studied, especially considering the atmospheric effects of clouds on FSO links. In this model, UAVs communicate with ground terminals (GTs), where UAVs are deployed inside the service boundary. In the presence of clouds, the service boundary will experience disparity in the FSO channel, and thus the UAV deployment will be constrained to places where there is little or no cloud attenuation to satisfy the target data rate. Therefore, several cloud properties (including irregularity in shape) have been considered in finding the communication feasible polygon (CFP). To perform convex optimization of the UAV trajectory, the CFP was transformed into convex subsets, and an algorithm that can find the largest inner convex CFP (ICCFP) is proposed. Using the maximum ICCFP area derived combined with an energy efficiency (EE) ratio maximization trajectory algorithm, the cloud avoidance convex area energy-efficient trajectory optimization (CA2ET) algorithm is formed. Numerical results show that the proposed CA2ET algorithm achieves significantly higher data rates and longer connection time between the GT and the UAV, compared to the existing EEMCT and LCFTM algorithms.
ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2024.3362952