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Experimental Demonstration and Performance Enhancement of 5G NR Multiband Radio over Fiber System Using Optimized Digital Predistortion

Authors :
Hadi, Muhammad Usman
Awais, Muhammad
Raza, Mohsin
Ashraf, Muhammad Ikram
Song, Jian
Hadi, Muhammad Usman
Awais, Muhammad
Raza, Mohsin
Ashraf, Muhammad Ikram
Song, Jian
Source :
Applied Sciences (Switzerland) vol.11 (2021) date: 2021-12-07 nr.24 p.e11624
Publication Year :
2021

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.

Details

Database :
OAIster
Journal :
Applied Sciences (Switzerland) vol.11 (2021) date: 2021-12-07 nr.24 p.e11624
Notes :
DOI: 10.3390/app112411624, English
Publication Type :
Electronic Resource
Accession number :
edsoai.on1358188105
Document Type :
Electronic Resource