Machine Learning for Performance Enhancement in Fronthaul Links for IOT Applications

Muhammad Usman Hadi, Abdul Basit

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

We present A-typical machine learning (ML) based digital predistortion (DPD) solution for performance enhancement in analog optical front-hauls (OFH) for internet of things (IoT) based applications. Volterra based DPD has been realized in the past which becomes quite cumbersome due to complexity and choice of coefficients. Whereas the traditional Artificial Neural Networks techniques require time and optimization to determine the best model configuration. The proposed support vector regression (SVR) method is used that alleviates the nonlinearities and uplifts the OFH performance optimally. In this work, the experimental evaluation is made for 5G new radio (NR) signal having 256 quadrature amplitude modulation using 1550 nm Mach Zehnder Modulator and dispersion compensation fiber having 1 km link length. The experimental results suggest that SVR-DPD results in performance enhancement as compared to traditional volterra methods such as generalized memory polynomial, hence proving to be exceptionally operational.

Original languageEnglish
Title of host publication2021 International Conference on Digital Futures and Transformative Technologies, ICoDT2 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665412858
ISBN (Print)9781665430746
DOIs
Publication statusPublished (in print/issue) - 20 May 2021
Event2021 International Conference on Digital Futures and Transformative Technologies, ICoDT2 2021 - Islamabad, Pakistan
Duration: 20 May 202121 May 2021

Publication series

Name2021 International Conference on Digital Futures and Transformative Technologies, ICoDT2 2021

Conference

Conference2021 International Conference on Digital Futures and Transformative Technologies, ICoDT2 2021
Country/TerritoryPakistan
CityIslamabad
Period20/05/2121/05/21

Bibliographical note

Publisher Copyright:
© 2021 IEEE.

Keywords

  • digital Predistortion
  • error vector magnitude
  • internet of things
  • machine learning

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