Suppression of Fiber Nonlinearities and PMD in Coded-Modulation Schemes With Coherent Detection by Using Turbo Equalization

Djordjević, Ivan B.; Minkov, L.L.; Xu, Lei; Wang, Ting

doi:10.1364/jocn.1.000555

Cited by 55 publications

(32 citation statements)

References 19 publications

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“…6, the number of states is equal to the finite field size for single parity check (SPC) code and the number of stages is determined by the check node degrees. For additional details about the BCJR algorithm, please refer to [15].…”

Section: Nonbinary Quasi-cyclic Ldpc Coding For 9-qammentioning

confidence: 99%

“…The former process is implemented by digital back-propagation scheme combined sliding-window MAP equalizer. Only a small number of coefficients are used in digital back-propagation scheme [15], just to reduce the channel memory so that the complexity of the MAP equalizer that follows is not too high. With the help of sliding-MAP equalizer and digital back propagation, the corresponding distribution is Gaussian-like, similar to back-to-back scenario.…”

Section: Advanced Coded Modulation Scheme For Non-uniform 9-qam Signamentioning

confidence: 99%

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Advanced GF(3^2) nonbinary LDPC coded modulation with non-uniform 9-QAM outperforming star 8-QAM

2016

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Abstract:In this paper, we first describe a 9-symbol non-uniform signaling scheme based on Huffman code, in which different symbols are transmitted with different probabilities. By using the Huffman procedure, prefix code is designed to approach the optimal performance. Then, we introduce an algorithm to determine the optimal signal constellation sets for our proposed non-uniform scheme with the criterion of maximizing constellation figure of merit (CFM). The proposed nonuniform polarization multiplexed signaling 9-QAM scheme has the same spectral efficiency as the conventional 8-QAM. Additionally, we propose a specially designed GF(3 2 ) nonbinary quasi-cyclic LDPC code for the coded modulation system based on the 9-QAM non-uniform scheme. Further, we study the efficiency of our proposed non-uniform 9-QAM, combined with nonbinary LDPC coding, and demonstrate by Monte Carlo simulation that the proposed GF(2 3 ) nonbinary LDPC coded 9-QAM scheme outperforms nonbinary LDPC coded uniform 8-QAM by at least 0.8dB. Peckham, "Coded PDM-OFDM transmission with shaped 256-iterative-polar-modulation achieving 11.15-b/s/Hz intrachannel spectral efficiency and 800-km reach," J. Lightwave Technol. 31(4), 538-545 (2013).

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Section: Nonbinary Quasi-cyclic Ldpc Coding For 9-qammentioning

confidence: 99%

Section: Advanced Coded Modulation Scheme For Non-uniform 9-qam Signamentioning

confidence: 99%

Advanced GF(3^2) nonbinary LDPC coded modulation with non-uniform 9-QAM outperforming star 8-QAM

2016

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“…The quest for ever higher transmission rates in single mode optical fiber transmission has directed research efforts to (i) compensation of fiber nonlinearities or (ii) considering them as additional noise that can be mitigated using strong forward error correction (FEC) schemes together with judicious choice of the transmitted constellation (coded modulation) [1][2][3]. In the first approach digital backpropagation (DBP) [4][5][6][7] has proved to be effective in mitigating nonlinear distortion and increasing the effective received signal-to-noise ratio (SNR) at the decision gate.…”

Section: Introductionmentioning

confidence: 99%

On the performance of multichannel digital backpropagation in high-capacity long-haul optical transmission

Liga¹,

Xu²,

Alvarado³

et al. 2014

Opt. Express

109

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“…The desire for high capacity fiber-optic networks has led to an adaptation of well-known digital communication and signal processing techniques [1] . The ultimate limit of any signal processing and coding scheme is the channel capacity.…”

Section: Introductionmentioning

confidence: 99%

“…The steps above are repeated until convergence or until the maximum number of iterations are reached. In the numerical results section, we apply the proposed method on a 64 iterative polarization quantization (IPQ) source [1] . The numerical results give a tighter bound on the capacity per single-polarization per channel.…”

mentioning

confidence: 99%

Determination of channel capacity and optimum source distribution of fiber-optic channel

Zhang

Djordjević

Batshon

et al. 2010

2010 12th International Conference on Transparent Optical Networks

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We describe a general engineering method to compute a tighter bound on fiber-optic channel capacity and the optimum source distribution. This method first determines the conditional probability density functions of an optical fiber channel by evaluating histograms, or by instantons or edgeworth expansion approach. Starting from any source distribution, we generate source and output sequences to estimate the information rate and calculate A-posteriori State-Transition Weight. The optimum source distribution is obtained by constrained stochastic Arimoto-Blahut algorithm. We apply the proposed methods on a 64 iterative polarization quantization source. The optimized capacity per single-polarization per channel is higher than achievable information rate. As the transmission distance increases the optimized distribution is changed from Gaussian-like distribution to nonGaussian-like distribution. This is due to the fact that the nonlinear interaction of ASE noise and Kerr nonlinearities cannot be compensated for by back-propagation method. INTRODUCTIONThe desire for high capacity fiber-optic networks has led to an adaptation of well-known digital communication and signal processing techniques [1] . The ultimate limit of any signal processing and coding scheme is the channel capacity. The capacity is an exciting theoretical challenge while considering the interaction of chromatic dispersion, PMD and fiber nonlinearities. The tighter bounds on channel capacity have substantially practical implications that known channel capacity reveals how much current signal processing and coding schemes can be improved. Many works estimated the nonlinear fiber channel capacity bounds in an approximate fashion [2]-[4] , using conservative estimate [5] or achievable information rate (AIR) [6] .In this paper, we describe a general engineering method to compute a tighter bound of the fiber channel capacity and the optimum source distribution on a given constellation. This method first models pulse energy propagation in long-haul optical fiber transmission systems to determine the probability density functions (pdfs) by evaluating histograms, or by using instantons or edgeworth expansion approach [6],[7] . The fiber nonlinearities, ASE noise-signal interaction during transmission and chromatic dispersion is taken into account in these pdfs. Starting from any source distribution, we generate the source and output sequences to estimate the information rate by applying the method originally proposed by Arnold [ 8 ] , Pfitser [ 9] or Kavcic [ 10 ] . We then calculate A-posteriori State-Transition Weight by forward-backward sum-product (Baum-Welch, BCJR) algorithm [8] or by expectation weight of stochastic Arimoto-Blahut algorithm [11] . The parameters to keep the input distribution within the constrains are computed by solving a nonlinear equation. The input distribution is updated by constrained stochastic Arimoto-Blahut algorithm. The steps above are repeated until convergence or until the maximum number of iterations are reached. In the n...

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Suppression of Fiber Nonlinearities and PMD in Coded-Modulation Schemes With Coherent Detection by Using Turbo Equalization

Cited by 55 publications

References 19 publications

Advanced GF(3^2) nonbinary LDPC coded modulation with non-uniform 9-QAM outperforming star 8-QAM

Advanced GF(3^2) nonbinary LDPC coded modulation with non-uniform 9-QAM outperforming star 8-QAM

On the performance of multichannel digital backpropagation in high-capacity long-haul optical transmission

Determination of channel capacity and optimum source distribution of fiber-optic channel

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