Multilevel PAM with ANN Equalization for an RC-LED SI-POF System

Isaac N.O. Osahon, Sujan Rajbhandari, Asim Ihsan, Jianming Tang, Wasiu O. Popoola

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In this experimental study, data transmission over step-index plastic optical fiber (SI-POF) is implemented with multilevel pulse amplitude modulation (PAM-M) scheme using a resonant cavity light emitting diode (RC-LED) as the optical transmitter. An artificial neural network (ANN) based equalizer is used in the RC-LED SI-POF system to jointly mitigate channel distortion and system non-linearities. Furthermore, the ANN equalizer's performance is compared to state-of-the-art equalizers used for the system - the Volterra equalizer and the decision feedback equalizer (DFE). The ANN equalizer offers the best bit rates compared to the others for the system with high non-linearities. For instance, at a BER of about 10-3, the ANN equalizer results in a bit rate of 780 Mbps, 710 Mbps, and 650 Mbps with PAM-2, PAM-4 and PAM-8 schemes, respectively. However, the Volterra equalizer results in a bit rate of 720 Mbps, 660 Mbps, and 580 Mbps with these PAM schemes, respectively. And with the DFE, the bit rates are 610 Mbps, 510 Mbps, and 120 Mbps, respectively.

Original languageEnglish
Title of host publication2023 IEEE 20th Consumer Communications and Networking Conference, CCNC 2023
PublisherInstitute of Electrical and Electronics Engineers
Pages481-484
Number of pages4
ISBN (Electronic)9781665497343
DOIs
Publication statusPublished - 17 Mar 2023
Event20th IEEE Consumer Communications and Networking Conference, CCNC 2023 - Las Vegas, United States
Duration: 8 Jan 202311 Jan 2023

Publication series

NameProceedings - IEEE Consumer Communications and Networking Conference, CCNC
Volume2023-January
ISSN (Print)2331-9860

Conference

Conference20th IEEE Consumer Communications and Networking Conference, CCNC 2023
Country/TerritoryUnited States
CityLas Vegas
Period8/01/2311/01/23

Keywords / Materials (for Non-textual outputs)

  • artificial neural network
  • Equalization
  • multi-layer perceptron
  • plastic optical fiber communication
  • pulse amplitude modulation
  • resonant cavity light emitting diode

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