Multiplier-Free Intrachannel Nonlinearity Compensating Algorithm Operating at Symbol Rate

Tao, Zhenning; Li, Dou; Yan, Weizhen; Li, Lei; Hoshida, Takeshi; Rasmussen, Jens C.

doi:10.1109/jlt.2011.2160933

Cited by 201 publications

(130 citation statements)

References 21 publications

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“…Here we developed a perturbative discrete-time channel model with finite memory based on the nonlinearity compensation technique proposed in [10] and experimentally demonstrated in [11][12]. The resulted multivariate channel model allows us to describe memory effects analytically, including both signal-signal and signal-noise effects.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…More accurate channel capacity estimations will require accurate modelling approaches that take into account the finite response of the nonlinear channel [7][8]. These can be also used for other applications such as coding [6] or pre/post-distortion [9-10] compensation, and suggest system designs that can improve significantly the transmission capacity [11][12].Here we developed a perturbative discrete-time channel model with finite memory based on the nonlinearity compensation technique proposed in [10] and experimentally demonstrated in [11][12]. The resulted multivariate channel model allows us to describe memory effects analytically, including both signal-signal and signal-noise effects.…”

mentioning

confidence: 99%

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Perturbative discrete-time multivariate fiber channel model with finite memory

Sorokina

Sygletos

Turitsyn

2016

2016 18th International Conference on Transparent Optical Networks (ICTON)

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We introduce a discrete-time fibre channel model that provides an accurate analytical description of signalsignal and signal-noise interference with memory defined by the interplay of nonlinearity and dispersion. Also the conditional pdf of signal distortion, which captures non-circular complex multivariate symbol interactions, is derived providing the necessary platform for the analysis of channel statistics and capacity estimations in fibre optic links. Keywords: discrete-time channel model, channel memory, nonlinear interference, Shannon capacity INTRODUCTIONAccurate description of fibre channel models is critically important for information theory analysis, coding, and digital signal processing techniques in future high capacity transmission systems [1]. Existing channel models [2][3][4][5] are based on averaging signal distortions via an infinite memory approximation [6] of the signal interactions, where they are considered to be nonlinear noise. As averaging leads to information loss about the signal interference, it results in a degraded lower bound of the system capacity in the highly nonlinear regime. More accurate channel capacity estimations will require accurate modelling approaches that take into account the finite response of the nonlinear channel [7][8]. These can be also used for other applications such as coding [6] or pre/post-distortion [9-10] compensation, and suggest system designs that can improve significantly the transmission capacity [11][12].Here we developed a perturbative discrete-time channel model with finite memory based on the nonlinearity compensation technique proposed in [10] and experimentally demonstrated in [11][12]. The resulted multivariate channel model allows us to describe memory effects analytically, including both signal-signal and signal-noise effects. Its accuracy has been compared against numerical simulations and the traditional Gaussian noise model approach, showing high accuracy in every operating regime of the transmission system. Finally, we derive an analytical expression of the conditional pdf that describes signal-interference in fiber-optic channels..

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

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Perturbative discrete-time multivariate fiber channel model with finite memory

Sorokina

Sygletos

Turitsyn

2016

2016 18th International Conference on Transparent Optical Networks (ICTON)

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“…Concurrently, nonlinear compensation (NLC) techniques based on DSP have been extensively investigated to improve robustness of the receivers against nonlinear impairments. In particular, digital backpropagation (DBP) [8], perturbation equalizers [9] and maximum likelihood sequence detection (MLSD) [10] have been explored.…”

Section: Introductionmentioning

confidence: 99%

Impairment mitigation in superchannels with digital backpropagation and MLSD

Silva¹,

Larsen²,

Zibar³

2015

Opt. Express

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We assess numerically the performance of single-carrier digital backpropagation (SC-DBP) and maximum-likelihood sequence detection (MLSD) for DP-QPSK and DP-16QAM superchannel transmission over dispersion uncompensated links for three different cases of spectral shaping: optical pre-filtering of RZ and NRZ spectra, and digital Nyquist filtering. We investigate the limits for carrier proximity of each spectral shaping technique and the correspondent performance behavior of each algorithm, for both modulation formats. For superchannels with carrier spacing close to the Nyquist limit, it is shown that the maximum performance improvement of 1.0 dB in Q 2 -factor is provided by those algorithms. However, such gain can be highly reduced when the order of the modulation format increases.

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“…It has been shown that nonlinear fibre impairments can be compensated by various techniques: digital backpropagation (DBP), maximum-likelihood sequence estimation, nonlinear polarization crosstalk cancelation, nonlinear pre-and post-compensation, RF-pilot, etc, [3][4][5][6][7] and references therein. Some of the mentioned methods suffer from complexity and, additionally, the achievable gain in the nonlinear tolerance is dependent on particular transmission scenarios.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear impairment compensation using expectation maximization for dispersion managed and unmanaged PDM 16-QAM transmission

Zibar¹,

Winther²,

Franceschi³

et al. 2012

Opt. Express

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Abstract:In this paper, we show numerically and experimentally that expectation maximization (EM) algorithm is a powerful tool in combating system impairments such as fibre nonlinearities, inphase and quadrature (I/Q) modulator imperfections and laser linewidth. The EM algorithm is an iterative algorithm that can be used to compensate for the impairments which have an imprint on a signal constellation, i.e. rotation and distortion of the constellation points. The EM is especially effective for combating non-linear phase noise (NLPN). It is because NLPN severely distorts the signal constellation and this can be tracked by the EM. The gain in the nonlinear system tolerance for the system under consideration is shown to be dependent on the transmission scenario. We show experimentally that for a dispersion managed polarization multiplexed 16-QAM system at 14 Gbaud a gain in the nonlinear system tolerance of up to 3 dB can be obtained. For, a dispersion unmanaged system this gain reduces to 0.5 dB.

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Multiplier-Free Intrachannel Nonlinearity Compensating Algorithm Operating at Symbol Rate

Cited by 201 publications

References 21 publications

Perturbative discrete-time multivariate fiber channel model with finite memory

Perturbative discrete-time multivariate fiber channel model with finite memory

Impairment mitigation in superchannels with digital backpropagation and MLSD

Nonlinear impairment compensation using expectation maximization for dispersion managed and unmanaged PDM 16-QAM transmission

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