2017
DOI: 10.1049/iet-com.2016.1115
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A novel support vector machine robust model based electrical equaliser for coherent optical orthogonal frequency division multiplexing systems

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Cited by 11 publications
(4 citation statements)
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“…Orthogonal frequency-division multiplexing (OFDM) is an emerging technology in optical fiber communications due to its inherent advantages, which include simplified digital signal processing for channel estimation and the compensation of linear fiber-induced impairments, such as chromatic dispersion and polarization-mode dispersion [1]. OFDM is essentially a method of encoding digital data on multiple carrier frequencies, harnessing the (inverse) fast Fourier transform (IFFT) [2], and is widely used in wireless local area networks (802.11 a/g) and wireless metropolitan area networks (802.16 d).…”
Section: Introductionmentioning
confidence: 99%
“…Orthogonal frequency-division multiplexing (OFDM) is an emerging technology in optical fiber communications due to its inherent advantages, which include simplified digital signal processing for channel estimation and the compensation of linear fiber-induced impairments, such as chromatic dispersion and polarization-mode dispersion [1]. OFDM is essentially a method of encoding digital data on multiple carrier frequencies, harnessing the (inverse) fast Fourier transform (IFFT) [2], and is widely used in wireless local area networks (802.11 a/g) and wireless metropolitan area networks (802.16 d).…”
Section: Introductionmentioning
confidence: 99%
“…Support vector regression (SVR), based on structural risk minimization, is a valid machine learning tool in dealing with small data blocks, which can be optimized to global minimum. In recent years, it has been used for channel equalization in single input single output (SISO) [29]- [32], orthogonal frequency division multiplexing (OFDM) [33], and MIMO systems [34]. Specifically, in [34], SVR framework combined with CMA and radius directed algorithm (RDA) is researched.…”
Section: Introductionmentioning
confidence: 99%
“…The decision-directed phase-locked loop (DDPLL) method was employed for the carrier phase recovery. Finally, the machine learning algorithm was processed before the hard decision and the bit error rate (BER)/Q-factor (=20log 10 √ 2er f c −1 (2BER) ) calculation, similarly to other reported work with machine learning signal processing [20][21][22][23][24][25].…”
mentioning
confidence: 99%