Performance of Location-Based Equalization for OFDM Indoor Visible Light Communications

Xiaodi You, Jian Chen, Changyuan Yu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

18 Citations (Scopus)

Abstract

In indoor visible light communication (VLC) systems, multiple optical transmitters and reflections will result in a dispersive multi-path channel. We propose a location-based equalization (LBE) method for indoor VLC using orthogonal frequency division multiplexing. With LBE, the location information of a VLC receiver, particularly in terms of coordinates, is utilized for channel estimation. The estimated channel parameters can be further used in a variety of ways for real-time mitigation of multi-path effects induced by a dispersive channel. As a result, the channel distortion can be predictable and thus VLC becomes a smart location-based value-added service. With different implementation schemes, extensive numerical simulations and comparisons are carried out to verify the feasibility of LBE. Results show that LBE can effectively improve system bit error rate (BER) performance at different indoor locations. Even in the presence of location error, link shadowing, or receiver tilt, the LBE design, especially based on only a line-of-sight channel, still shows good robustness, which can achieve reliable transmission quality with BER < 10-3 at various locations. With LBE, the horizontal and vertical tolerance against location error can be 0.28 m and 0.1 m, respectively, while the tolerance angle against receiver tilt is basically no less than 30°.

Original languageEnglish
Article number8826240
Pages (from-to)1229-1243
Number of pages15
JournalIEEE Transactions on Cognitive Communications and Networking
Volume5
Issue number4
DOIs
Publication statusPublished - Dec 2019

Keywords

  • light-emitting diode
  • location-based equalization
  • orthogonal frequency division multiplexing
  • Visible light communication

ASJC Scopus subject areas

  • Hardware and Architecture
  • Computer Networks and Communications
  • Artificial Intelligence

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