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Assessment of digital predistortion methods for DFB‐SSMF radio‐over‐fiber links linearization

Authors :
Muhammad Usman Hadi
Olivier Venard
Giovanni Tartarini
Jean-Luc Polleux
Chouaib Kantana
Pier A. Traverso
Genevieve Baudoin
Alma Mater Studiorum Università di Bologna [Bologna] (UNIBO)
Electronique, Systèmes de communication et Microsystèmes (ESYCOM)
Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Université Paris-Est Marne-la-Vallée (UPEM)-ESIEE Paris
ESIEE Paris
Hadi M.U.
Kantana C.
Traverso P.A.
Tartarini G.
Venard O.
Baudoin G.
Polleux J.-L.
Conservatoire National des Arts et Métiers [CNAM] (CNAM)
HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Paris-Est Marne-la-Vallée (UPEM)-ESIEE Paris
Source :
Microwave and Optical Technology Letters, Microwave and Optical Technology Letters, Wiley, 2020, ⟨10.1002/mop.32073⟩
Publication Year :
2019
Publisher :
Wiley, 2019.

Abstract

This letter presents a comparative evaluation between three different behavioral models to perform digital predistortion (DPD) that enhances the linearity of radio-over-fiber (RoF)-based front haul links for the mobile network. In particular, the intention is to jump out of the volterra box and propose models based on segmentation approach. Especially the decomposed vector rotation (DVR) model is compared to volterra polynomials such as memory and generalized memory polynomial (GMP) architectures. DPD is employed to RoF links that are based on distributed feedback laser emitting at 1310 nm, and standard single-mode fiber for long-term evolution 20-MHz signal with 256-QAM modulation format. The effectiveness of the digital predistortion methodology is investigated for varying input powers in terms of normalized mean square error, adjacent channel power ratio, and error vector magnitude. The experimental results demonstrate that DVR achieves elevated linearization when compared to memory polynomial and GMP models.

Details

ISSN :
10982760 and 08952477
Volume :
62
Database :
OpenAIRE
Journal :
Microwave and Optical Technology Letters
Accession number :
edsair.doi.dedup.....d3720154d763ba6e3cbddc378b20475c
Full Text :
https://doi.org/10.1002/mop.32073