Deep Learning Framework for Wireless Systems: Applications to Optical Wireless Communications

Hoon Lee, Sang Hyun Lee, Tony Q.S. Quek, Inkyu Lee

Research output: Contribution to journalArticlepeer-review

44 Citations (Scopus)

Abstract

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.

Original languageEnglish
Article number8663989
Pages (from-to)35-41
Number of pages7
JournalIEEE Communications Magazine
Volume57
Issue number3
DOIs
Publication statusPublished - 2019 Mar

Bibliographical note

Funding Information:
This work was supported by the National Research Foun dation through the Ministry of Science, ICT and Future Planning (MSIP), South Kore an Government, under Grant 2017R1A2B3012316. The work of S. H. Lee was sup ported in part by Institute for Information & communica tions Technology Promotion (IITP) grant funded by the Korea government (MSIT) (2016-0-00208, High Accurate Positioning Enabled MIMO Transmission and Network Technologies for Next 5G-V2X (vehicle-to-everything) Ser vices). The work of T. Q. S. Quek was supported by the SUTD-ZJU Research Collabo ration under Grant SUTD-ZJU/ RES/05/2016.

Funding Information:
This work was supported by the National Research Foundation through the Ministry of Science, ICT and Future Planning (MSIP), South Korean Government, under Grant 2017R1A2B3012316. The work of S. H. Lee was supported in part by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (2016-0-00208, High Accurate Positioning Enabled MIMO Transmission and Network Technologies for Next 5G-V2X (vehicle-to-everything) Services). The work of T. Q. S. Quek was supported by the SUTD-ZJU Research Collaboration under Grant SUTD-ZJU/RES/05/2016.

Publisher Copyright:
© 2019 IEEE.

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

Fingerprint

Dive into the research topics of 'Deep Learning Framework for Wireless Systems: Applications to Optical Wireless Communications'. Together they form a unique fingerprint.

Cite this