An improved deep learning-based end-to-end autoencoder for UAV-to-ground free space optical communication-Reference-Cited by-同舟云学术

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An improved deep learning-based end-to-end autoencoder for UAV-to-ground free space optical communication

Published:2023-12 Issue: Volume:549 Page:129938
ISSN:0030-4018
Container-title:Optics Communications
language:en
Short-container-title:Optics Communications

Author:

Zhang Qianwu^ORCID,Chen Guanwen,Liu Boyang,Zhi Xuzhuang,Zhan Shucheng,Zhang Jing,Cao Bingyao,Li Zhengxuan

Funder

Science and Technology Commission of Shanghai Municipality

National Key Research and Development Program of China

Higher Education Discipline Innovation Project

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Physical and Theoretical Chemistry,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials

Reference27 articles.

1. Optical communication in space: challenges and mitigation techniques;Kaushal;IEEE Commun. Surv. & Tutor.,2017

2. Survey on free space optical communication: a communication theory perspective;Khalighi;IEEE Commun. Surv. & Tutor.,2014

3. Emerging optical wireless communications-advanced and challenges;Ghassemlooy;IEEE J. Sel. Area. Commun.,2015

4. Investigations on free space optics communication system;Vigneshwaran,2013

5. Ground-to-Air FSO communications: when high data rate communication meets efficient energy harvesting with simple designs;Abou-Rjeily;Opt Express,2019

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