Nonlinear Probabilistic Constellation Shaping with Sequence Selection

Probabilistic shaping is a pragmatic approach to improve the performance of coherent optical fiber communication systems. In the nonlinear regime, the advantages offered by probabilistic shaping might increase thanks to the opportunity to obtain an additional nonlinear shaping gain. Unfortunately, the optimization of conventional shaping techniques, such as probabilistic amplitude shaping (PAS), yields a relevant nonlinear shaping gain only in scenarios of limited practical interest. In this manuscript we use sequence selection to investigate the potential, opportunities, and challenges offered by nonlinear probabilistic shaping. First, we show that ideal sequence selection is able to provide up to 0.13 bit/s/Hz gain with respect to PAS with an optimized blocklength. However, this additional gain is obtained only if the selection metric accounts for the signs of the symbols: they must be known to compute the selection metric, but there is no need to shape them. Furthermore, we show that the selection depends in a non-critical way on the symbol rate and link length: the sequences selected for a certain scenario still provide a relevant gain if these are modified. Then, we analyze and compare several practical implementations of sequence selection by taking into account interaction with forward error correction (FEC) and complexity. Overall, the single block and the multi block FEC-independent bit scrambling are the best options, with a gain up to 0.08 bit/s/Hz. The main challenge and limitation to their practical implementation remains the evaluation of the metric, whose complexity is currently too high. Finally, we show that the nonlinear shaping gain provided by sequence selection persists when carrier phase recovery is included.

[1]  E. Forestieri,et al.  Probabilistic Shaping Methods for Linear and Nonlinear Channels , 2023, 2023 Optical Fiber Communications Conference and Exhibition (OFC).

[2]  E. Forestieri,et al.  Practical Implementation of Sequence Selection for Nonlinear Probabilistic Shaping , 2022, 2023 Optical Fiber Communications Conference and Exhibition (OFC).

[3]  E. Forestieri,et al.  On the Nonlinear Shaping Gain With Probabilistic Shaping and Carrier Phase Recovery , 2022, Journal of Lightwave Technology.

[4]  L. Lampe,et al.  Nonlinearity Tolerant Shaping with Sequence Selection , 2022, 2022 European Conference on Optical Communication (ECOC).

[5]  L. Lampe,et al.  Probabilistic Amplitude Shaping and Nonlinearity Tolerance: Analysis and Sequence Selection Method , 2022, Journal of Lightwave Technology.

[6]  Reza Rafie Borujeny,et al.  Why Constant-Composition Codes Reduce Nonlinear Interference Noise , 2022, Journal of Lightwave Technology.

[7]  Paparao Palacharla,et al.  Mitigating Nonlinear Interference by Limiting Energy Variations in Sphere Shaping , 2022, 2022 Optical Fiber Communications Conference and Exhibition (OFC).

[8]  Marco Secondini,et al.  New Lower Bounds on the Capacity of Optical Fiber Channels via Optimized Shaping and Detection , 2021, Journal of Lightwave Technology.

[9]  Alex Alvarado,et al.  List-Encoding CCDM: A Nonlinearity-Tolerant Shaper Aided by Energy Dispersion Index , 2021, Journal of Lightwave Technology.

[10]  G. Raybon,et al.  Shaping lightwaves in time and frequency for optical fiber communication , 2021, Nature Communications.

[11]  Yunus Can Gültekin,et al.  Exponentially-Weighted Energy Dispersion Index for the Nonlinear Interference Analysis of Finite-Blocklength Shaping , 2021, 2021 European Conference on Optical Communication (ECOC).

[12]  Marco Secondini,et al.  A Sequence Selection Bound for the Capacity of the Nonlinear Fiber Channel , 2021, 2021 European Conference on Optical Communication (ECOC).

[13]  Yunus Can Gültekin,et al.  Kurtosis-Limited Sphere Shaping for Nonlinear Interference Noise Reduction in Optical Channels , 2021, Journal of Lightwave Technology.

[14]  F. Willems,et al.  Temporal Energy Analysis of Symbol Sequences for Fiber Nonlinear Interference Modelling via Energy Dispersion Index , 2021, Journal of Lightwave Technology.

[15]  Marco Secondini,et al.  Interplay of Probabilistic Shaping and Carrier Phase Recovery for Nonlinearity Mitigation , 2020, 2020 European Conference on Optical Communications (ECOC).

[16]  Marco Secondini,et al.  Hierarchical Distribution Matching for Probabilistic Amplitude Shaping † , 2020, Entropy.

[17]  Jorg-Peter Elbers,et al.  Mitigating Fiber Nonlinearities by Short-Length Probabilistic Shaping , 2020, 2020 Optical Fiber Communications Conference and Exhibition (OFC).

[18]  M. Secondini,et al.  Hierarchical Distribution Matching: A Versatile Tool for Probabilistic Shaping , 2019, Optical Fiber Communications Conference and Exhibition.

[19]  Yunus Can Gültekin,et al.  Probabilistic Shaping for Finite Blocklengths: Distribution Matching and Sphere Shaping , 2019, Entropy.

[20]  Tadashi Ikeuchi,et al.  Introducing Enumerative Sphere Shaping for Optical Communication Systems With Short Blocklengths , 2019, Journal of Lightwave Technology.

[21]  Peter J. Winzer,et al.  Probabilistic Constellation Shaping for Optical Fiber Communications , 2019, Journal of Lightwave Technology.

[22]  Erik Agrell,et al.  Hierarchical Distribution Matching for Probabilistically Shaped Coded Modulation , 2018, Journal of Lightwave Technology.

[23]  Frans M. J. Willems,et al.  Approximate Enumerative Sphere Shaping , 2018, 2018 IEEE International Symposium on Information Theory (ISIT).

[24]  Frans M. J. Willems,et al.  On constellation shaping for short block lengths , 2018 .

[25]  Toshiaki Koike-Akino,et al.  Multiset-Partition Distribution Matching , 2018, IEEE Transactions on Communications.

[26]  Frans M. J. Willems,et al.  Constellation shaping for IEEE 802.11 , 2017, 2017 IEEE 28th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).

[27]  Alex Alvarado,et al.  Achievable Information Rates for Fiber Optics: Applications and Computations , 2017, Journal of Lightwave Technology.

[28]  Marco Secondini,et al.  Scope and Limitations of the Nonlinear Shannon Limit , 2017, Journal of Lightwave Technology.

[29]  Ronen Dar,et al.  A Shaping Algorithm for Mitigating Inter-Channel Nonlinear Phase-Noise in Nonlinear Fiber Systems , 2016, Journal of Lightwave Technology.

[30]  Georg Böcherer,et al.  On Probabilistic Shaping of Quadrature Amplitude Modulation for the Nonlinear Fiber Channel , 2016, Journal of Lightwave Technology.

[31]  Patrick Schulte,et al.  Rate Adaptation and Reach Increase by Probabilistically Shaped 64-QAM: An Experimental Demonstration , 2016, Journal of Lightwave Technology.

[32]  Patrick Schulte,et al.  Constant Composition Distribution Matching , 2015, IEEE Transactions on Information Theory.

[33]  Patrick Schulte,et al.  Bandwidth Efficient and Rate-Matched Low-Density Parity-Check Coded Modulation , 2015, IEEE Transactions on Communications.

[34]  Rudolf Mathar,et al.  Operating LDPC codes with zero shaping gap , 2011, 2011 IEEE Information Theory Workshop.

[35]  R. Noe,et al.  Hardware-Efficient Coherent Digital Receiver Concept With Feedforward Carrier Recovery for $M$ -QAM Constellations , 2009, Journal of Lightwave Technology.

[36]  Frank R. Kschischang,et al.  Optimal nonuniform signaling for Gaussian channels , 1993, IEEE Trans. Inf. Theory.

[37]  A. Robert Calderbank,et al.  Nonequiprobable signaling on the Gaussian channel , 1990, IEEE Trans. Inf. Theory.

[38]  Sang Joon Kim,et al.  A Mathematical Theory of Communication , 2006 .

[39]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[40]  C.E. Shannon,et al.  Communication in the Presence of Noise , 1949, Proceedings of the IRE.