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Hadi, Muhammad Usman, Awais, Muhammad 
ORCID: https://orcid.org/0000-0001-6421-9245, Raza, Mohsin, Ashraf, Muhammad Ikram and Song, Jian
(2021)
Experimental demonstration and performance enhancement of 5G NR multiband radio over fiber system using optimized digital predistortion.
Applied Sciences, 11 (24).
ISSN 2076-3417
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Abstract
This paper presents an experimental realization of multiband 5G new radio (NR) optical front haul (OFH) based radio over fiber (RoF) system using digital predistortion (DPD). A novel magnitude-selective affine (MSA) based DPD method is proposed for the complexity reduction and performance enhancement of RoF link followed by its comparison with the canonical piece wise linearization (CPWL), decomposed vector rotation method (DVR) and generalized memory polynomial (GMP) methods. Similarly, a detailed study is shown followed by the implementation proposal of novel neural network (NN) for DPD followed by its comparison with MSA, CPWL, DVR and GMP methods. In the experimental testbed, 5G NR standard at 20 GHz with 50 MHz bandwidth and flexible-waveform signal at 3 GHz with 20 MHz bandwidth is used to cover enhanced mobile broad band and small cells scenarios. A dual drive Mach Zehnder Modulator having two distinct radio frequency signals modulates a 1310 nm optical carrier using distributed feedback laser for 22 km of standard single mode fiber. The experimental results are presented in terms of adjacent channel power ratio (ACPR), error vector magnitude (EVM), number of estimated coefficients and multiplications. The study aims to identify those novel methods such as MSA DPD are a good candidate to deploy in real time scenarios for DPD in comparison to NN based DPD which have a slightly better performance as compared to the proposed MSA method but has a higher complexity levels. Both, proposed methods, MSA and NN are meeting the 3GPP Release 17 requirements.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | adjacent channel power ratio,digital predistortion,error vector magnitude,magnitude selective affine,neural network,radio over fiber,materials science(all),instrumentation,engineering(all),process chemistry and technology,computer science applications,fluid flow and transfer processes ,/dk/atira/pure/subjectarea/asjc/2500 |
| Faculty \ School: | Faculty of Science > School of Computing Sciences |
| UEA Research Groups: | Faculty of Science > Research Groups > Data Science and AI |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 17 Oct 2023 00:44 |
| Last Modified: | 10 Dec 2024 01:42 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/93301 |
| DOI: | 10.3390/app112411624 |
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