TR2020-050

Parallel-Amplitude Architecture and Subset Ranking for Fast Distribution Matching


    •  Fehenberger, T., Millar, D.S., Koike-Akino, T., Kojima, K., Parsons, K., "Parallel-Amplitude Architecture and Subset Ranking for Fast Distribution Matching", IEEE Transactions on Communications, DOI: 10.1109/​TCOMM.2020.2966693, Vol. 68, No. 4, pp. 1981-1990, April 2020.
      BibTeX TR2020-050 PDF
      • @article{Fehenberger2020apr,
      • author = {Fehenberger, Tobias and Millar, David S. and Koike-Akino, Toshiaki and Kojima, Keisuke and Parsons, Kieran},
      • title = {Parallel-Amplitude Architecture and Subset Ranking for Fast Distribution Matching},
      • journal = {IEEE Transactions on Communications},
      • year = 2020,
      • volume = 68,
      • number = 4,
      • pages = {1981--1990},
      • month = apr,
      • doi = {10.1109/TCOMM.2020.2966693},
      • issn = {1558-0857},
      • url = {https://www.merl.com/publications/TR2020-050}
      • }
  • MERL Contacts:
  • Research Areas:

    Communications, Optimization, Signal Processing

Abstract:

A distribution matcher (DM) maps a binary input sequence into a block of nonuniformly distributed symbols. To facilitate the implementation of shaped signaling, fast DM solutions with high throughput and low serialism are required. We propose a novel DM architecture with parallel amplitudes (PA-DM) for which m - 1 component DMs, each with a different binary output alphabet, are operated in parallel in order to generate a shaped sequence with m amplitudes. With negligible rate loss compared to a single nonbinary DM, PA-DM has a parallelization factor that grows linearly with m, and the component DMs have reduced output lengths. For such binary-output DMs, a novel constant-composition DM (CCDM) algorithm based on subset ranking (SR) is proposed. We present SR-CCDM algorithms that are serial in the minimum number of occurrences of either binary symbol for mapping, and fully parallel for demapping. For distributions that are optimized for the additive white Gaussian noise (AWGN) channel, we numerically show that PA-DM combined with SR-CCDM can reduce the number of sequential processing steps by more than an order of magnitude, while having a rate loss that is comparable to conventional nonbinary CCDM with arithmetic coding.

 

  • Related Publication

  •  Fehenberger, T., Millar, D.S., Koike-Akino, T., Kojima, K., Parsons, K., "Parallel-Amplitude Architecture and Subset Ranking for Fast Distribution Matching", arXiv, March 2019.
    BibTeX arXiv
    • @article{Fehenberger2019mar,
    • author = {Fehenberger, Tobias and Millar, David S. and Koike-Akino, Toshiaki and Kojima, Keisuke and Parsons, Kieran},
    • title = {Parallel-Amplitude Architecture and Subset Ranking for Fast Distribution Matching},
    • journal = {arXiv},
    • year = 2019,
    • month = mar,
    • url = {https://arxiv.org/abs/1902.08556}
    • }