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.

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

Hadi M. U.
Writing – Original Draft Preparation
;
Traverso P. A.
Methodology
;
Tartarini G.
Supervision
;
2020

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.
Hadi M.U.; Kantana C.; Traverso P.A.; Tartarini G.; Venard O.; Baudoin G.; Polleux J.-L.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/716294
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