On probabilistic shaping of Quadrature Amplitude Modulation for the nonlinear fiber channel

T. Fehenberger, A. Alvarado, G. Böcherer, N. Hanik

Research output: Contribution to journalArticleAcademicpeer-review

292 Citations (Scopus)


Different aspects of probabilistic shaping for a multispan optical communication system are studied. First, a numerical analysis of the additive white Gaussian noise (AWGN) channel investigates the effect of using a small number of input probability mass functions (PMFs) for a range of signal-to-noise ratios (SNRs), instead of optimizing the constellation shaping for each SNR. It is shown that if a small penalty of at most 0.1 dB SNR to the full shaping gain is acceptable, just two shaped PMFs are required per quadrature amplitude modulation (QAM) over a large SNR range. For a multispan wavelength division multiplexing optical fiber system with 64QAM input, it is shown that just one PMF is required to achieve large gains over uniform input for distances from 1400 to 3000 km. Using recently developed theoretical models that extend the Gaussian noise (GN) model and full-field split-step simulations, we illustrate the ramifications of probabilistic shaping on the effective SNR after fiber propagation. Our results show that, for a fixed average optical launch power, a shaping gain is obtained for the noise contributions from fiber amplifiers and modulation-independent nonlinear interference (NLI), whereas shaping simultaneously causes a penalty as it leads to an increased NLI. However, this nonlinear shaping loss is found to have a relatively minor impact, and optimizing the shaped PMF with a modulation-dependent GN model confirms that the PMF found for AWGN is also a good choice for a multi-span fiber system.
Original languageEnglish
Pages (from-to)5063-5073
JournalJournal of Lightwave Technology
Issue number21
Publication statusPublished - 1 Nov 2016


  • Achievable information rates
  • bit-wise decoders
  • Gaussian noise models
  • mutual information
  • nonlinear fiber channel
  • probabilistic shaping
  • wavelength division multiplexing


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