Open AccessBit-based support vector machine nonlinear detector for millimeter-wave radio-over-fiber mobile fronthaul systems
Author(s) -
Yue Cui,
Min Zhang,
Danshi Wang,
Siming Liu,
Ze Li,
GeeKung Chang
Publication year - 2017
Publication title -
optics express
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.25.026186
Subject(s) - radio over fiber , support vector machine , computer science , detector , quadrature amplitude modulation , extremely high frequency , phase shift keying , nonlinear system , electronic engineering , modulation (music) , artificial intelligence , bit error rate , telecommunications , algorithm , optical fiber , channel (broadcasting) , physics , engineering , quantum mechanics , acoustics
An effective bit-based support vector machine (SVM) is proposed as a non-parameter nonlinear mitigation approach in the millimeter-wave radio-over-fiber (RoF) mobile fronthaul (MFH) system for various modulation formats. First, we analyze the impairments originated from nonlinearities in the millimeter-wave RoF system. Then we introduce the operation principle of the bit-based SVM detector. As a classifier, the SVM can create nonlinear decision boundaries by kernel function to mitigate the distortions caused by both linear and nonlinear noise. In our design, SVM can learn and capture the link characteristics from only a few training data without requiring the prior estimation of the system link. The bit-based SVM only needs log 2 M SVMs to detect the signal of M-order modulation format. Experimental results have been obtained to verify the feasibility of the proposed method. The sensitivities are improved by 1.2-dB for 16-QAM, 1.3-dB for 64-QAM, 1.8-dB for 16-APSK and 1.3-dB for 32-APSK at BER = 1E-3 with SVM detector, respectively. The proposed bit-based SVM gains a large improvement in the nonlinear system tolerance and outperforms the system employing k-means algorithm.