2018/12/12 by Hoon Lee, Lee, Hoon, Sang Hyun Lee +5
Engineering · Medicine · #Advanced Photonic Communication Systems #Advanced Wireless Communication Technologies #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Information Theory (cs.IT) #Machine Learning (cs.LG) #Ocular and Laser Science Research #Optical Wireless Communication Technologies
paper · pdf · doi:10.48550/arxiv.1812.05227
openalex publication_date 2018/12/12 · openalex created_date 2022/08/01 · openalex updated_date 2026/07/28
Optical wireless communication (OWC) is a promising technology for future\nwireless communications owing to its potentials for cost-effective network\ndeployment and high data rate. There are several implementation issues in the\nOWC which have not been encountered in radio frequency wireless communications.\nFirst, practical OWC transmitters need an illumination control on color,\nintensity, and luminance, etc., which poses complicated modulation design\nchallenges. Furthermore, signal-dependent properties of optical channels raise\nnon-trivial challenges both in modulation and demodulation of the optical\nsignals. To tackle such difficulties, deep learning (DL) technologies can be\napplied for optical wireless transceiver design. This article addresses recent\nefforts on DL-based OWC system designs. A DL framework for emerging image\nsensor communication is proposed and its feasibility is verified by simulation.\nFinally, technical challenges and implementation issues for the DL-based\noptical wireless technology are discussed.\n