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A Neural Network Based Joint CFO-SCO Equalization for OFDM-RoF in Multi-Band Mobile Fronthaul
Conference paper

A Neural Network Based Joint CFO-SCO Equalization for OFDM-RoF in Multi-Band Mobile Fronthaul

Jhih-Heng Yan, Jia-Shiang Tseng, Sheng-Chen Tsai and Kai-Ming Feng
25th Opto-Electronics and Communications Conference, OECC 2020, 9273585
10/2020
DOI: https://doi.org/10.1109/OECC48412.2020.9273585
Appears in  keyword about Physics

Abstract

5G carrier frequency offset (CFO) machine learning millimeter wave mobile fronthaul multi-service neural network orthogonal frequency division multiplexing (OFDM) radio over fiber (RoF) sampling clock offset (SCO) Computer Networks and Communications Electrical and Electronic Engineering Electronic Optical and Magnetic Materials Instrumentation Atomic and Molecular Physics and Optics
A neural-network based machine learning joint CFO-SCO equalizer is proposed for 5G multi-service mobile fronthaul. Up-to 100 ppm CFO and 100 ppm SCO are compensated without conventional synchronization on time or frequency domain.

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