Information Rates and Error Exponents for Probabilistic Amplitude Shaping

Probabilistic Amplitude Shaping (PAS) is a codedmodulation scheme in which the encoder is a concatenation of a distribution matcher with a systematic Forward Error Correction (FEC) code. For reduced computational complexity the decoder can be chosen as a concatenation of a mismatched FEC decoder and dematcher. This work studies the theoretic limits of PAS. The classical joint source-channel coding (JSCC) setup is modified to include systematic FEC and the mismatched FEC decoder. At each step error exponents and achievable rates for the corresponding setup are derived.

[1]  Xi Chen,et al.  Trans-Atlantic Field Trial Using High Spectral Efficiency Probabilistically Shaped 64-QAM and Single-Carrier Real-Time 250-Gb/s 16-QAM , 2018, Journal of Lightwave Technology.

[2]  G. David Forney Trellis shaping , 1992, IEEE Trans. Inf. Theory.

[3]  Robert F. H. Fischer,et al.  Multilevel codes: Theoretical concepts and practical design rules , 1999, IEEE Trans. Inf. Theory.

[4]  Patrick Schulte,et al.  Field Trial of a 1 Tb/s Super-Channel Network Using Probabilistically Shaped Constellations , 2017, Journal of Lightwave Technology.

[5]  Fabian Steiner,et al.  Comparison of Geometric and Probabilistic Shaping with Application to ATSC 3.0 , 2016, ArXiv.

[6]  Georg Böcherer,et al.  Informational divergence and entropy rate on rooted trees with probabilities , 2013, 2014 IEEE International Symposium on Information Theory.

[7]  C. E. SHANNON,et al.  A mathematical theory of communication , 1948, MOCO.

[8]  Bernhard C. Geiger,et al.  Optimal Quantization for Distribution Synthesis , 2013, IEEE Transactions on Information Theory.

[9]  Imre Csiszár,et al.  Channel capacity for a given decoding metric , 1995, IEEE Trans. Inf. Theory.

[10]  Amirhossein Ghazisaeidi,et al.  Advanced C+L-Band Transoceanic Transmission Systems Based on Probabilistically Shaped PDM-64QAM , 2017, Journal of Lightwave Technology.

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

[12]  Junji Shikata,et al.  Information Theoretic Security for Encryption Based on Conditional Rényi Entropies , 2013, ICITS.

[13]  Shlomo Shamai,et al.  The empirical distribution of good codes , 1997, IEEE Trans. Inf. Theory.

[14]  Alexandre Graell i Amat,et al.  Probabilistically-Shaped Coded Modulation with Hard Decision Decoding and Staircase Codes , 2017, ArXiv.

[15]  Georg Böcherer Achievable Rates for Probabilistic Shaping , 2017, ArXiv.

[16]  D. A. Bell,et al.  Information Theory and Reliable Communication , 1969 .

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

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

[19]  Robert G. Gallager,et al.  A simple derivation of the coding theorem and some applications , 1965, IEEE Trans. Inf. Theory.

[20]  Thomas M. Cover,et al.  Elements of information theory (2. ed.) , 2006 .