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

37 Citations (Scopus)


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
Issue number3
Publication statusPublished - 2019 Mar

ASJC Scopus subject areas

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


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