2019
DOI: 10.1109/jlt.2019.2917308
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Non-Linear Phase Noise Mitigation Over Systems Using Constellation Shaping

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Cited by 26 publications
(14 citation statements)
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“…This is due to the larger ratio between the variance of the short-correlated NLPN and the one of the Gaussian noise component, which requires a finer phase estimation in order to approach the constellation obtained after ideal PN cancellation. In this condition, a less hardware intensive approach could be the implementation of an uncorrelated PN aware soft decoding strategy as proposed in [3]. Finally, for medium transmission distance with Np = 16 similar results to the long-haul case are observed, while with Np = 64 we clearly observe a region in which SS-VW and DS CPR are able to approach the theoretical phase noise mitigation with less than 0.1 dB SNR penalty.…”
Section: Analysis and Resultssupporting
confidence: 63%
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“…This is due to the larger ratio between the variance of the short-correlated NLPN and the one of the Gaussian noise component, which requires a finer phase estimation in order to approach the constellation obtained after ideal PN cancellation. In this condition, a less hardware intensive approach could be the implementation of an uncorrelated PN aware soft decoding strategy as proposed in [3]. Finally, for medium transmission distance with Np = 16 similar results to the long-haul case are observed, while with Np = 64 we clearly observe a region in which SS-VW and DS CPR are able to approach the theoretical phase noise mitigation with less than 0.1 dB SNR penalty.…”
Section: Analysis and Resultssupporting
confidence: 63%
“…Finally it is interesting to understand the relative weight of the NLIN dynamics and of the incomplete mitigation of the linear phase noise on the achievable performance observed with the proposed CPR. This information can in fact provide a quantification of the improvement which is possible to obtain by using additional DSP designed specifically for handling short-correlated NLPN as in [3]. For this purpose we apply DS CPR in the case of a linear channel in which, to perform a fair comparison, the ASE power after each span is properly adjusted to match the whole ResN+ASE power observed in the two cases previously presented after ideal phase noise removal.…”
Section: Figure 1 (Ac) Snr After the Proposed Cpr Implementations Amentioning
confidence: 99%
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“…Furthermore, the studies in [ and [20] proposed heuristic design methods to increase the constellation's robustness in a phase noise dominated channel. Alternatively, the work in [21] demonstrated significant reach gains by using the PCAWGN model in non-linear channel transmission for both probabilistic and geometrically shaped (GS) formats. Lastly, a recent study in [22] looked at employing end-to-end deep learning model to geometrically shape phase noise-robust multi-dimensional constellations for optical communications in PCAWGN channel.…”
mentioning
confidence: 99%