Journal
IEEE COMMUNICATIONS MAGAZINE
Volume 57, Issue 3, Pages 35-41Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/MCOM.2019.1800584
Keywords
-
Funding
- National Research Foundation through the Ministry of Science, ICT and Future Planning (MSIP), South Korean Government [2017R1A2B3012316]
- Institute for Information & communications Technology Promotion (IITP) - Korea government (MSIT) [2016-0-00208]
- SUTD-ZJU Research Collaboration [SUTD-ZJU/RES/05/2016]
Ask authors/readers for more resources
Optical wireless communication (OWC) is a promising technology for future wireless communications due to its potential for cost-effective network deployment and high data rate. There are several implementation issues in OWC that have not been encountered in radio frequency wireless communications. First, practical OWC transmitters need illumination control on color, intensity, luminance, and so on, which poses complicated modulation design challenges. Furthermore, signal-dependent properties of optical channels raise nontrivial challenges in both modulation and demodulation of the optical signals. To tackle such difficulties, deep learning (DL) technologies can be applied for optical wireless transceiver design. This article addresses recent efforts on DL-based OWC system designs. A DL framework for emerging image sensor communication is proposed, and its feasibility is verified by simulation. Finally, technical challenges and implementation issues for the DL-based optical wireless technology are discussed.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available