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Hierarchical Distribution Matching for Probabilistic Amplitude Shaping †
Probabilistic amplitude shaping—implemented through a distribution matcher (DM)—is an effective approach to enhance the performance and the flexibility of bandwidth-efficient coded modulations. Different DM structures have been proposed in the literature. Typically, both their performance and their...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7597263/ https://www.ncbi.nlm.nih.gov/pubmed/33286727 http://dx.doi.org/10.3390/e22090958 |
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author | Civelli, Stella Secondini, Marco |
author_facet | Civelli, Stella Secondini, Marco |
author_sort | Civelli, Stella |
collection | PubMed |
description | Probabilistic amplitude shaping—implemented through a distribution matcher (DM)—is an effective approach to enhance the performance and the flexibility of bandwidth-efficient coded modulations. Different DM structures have been proposed in the literature. Typically, both their performance and their complexity increase with the block length. In this work, we present a hierarchical DM (Hi-DM) approach based on the combination of several DMs of different possible types, which provides the good performance of long DMs with the low complexity of several short DMs. The DMs are organized in layers. Each upper-layer DM encodes information on a sequence of lower-layer DMs, which are used as “virtual symbols”. First, we describe the Hi-DM structure, its properties, and the encoding and decoding procedures. Then, we present three particular Hi-DM configurations, providing some practical design guidelines, and investigating their performance in terms of rate loss and energy loss. Finally, we compare the system performance obtained with the proposed Hi-DM structures and with their single-layer counterparts: a [Formula: see text] SNR gain is obtained by a two-layer Hi-DM based on constant composition DMs (CCDM) compared to a single-layer CCDM with same complexity; a [Formula: see text] gain and a significant complexity reduction are obtained by a Hi-DM based on minimum-energy lookup tables compared to a single-layer DM based on enumerative sphere shaping with same memory requirements. |
format | Online Article Text |
id | pubmed-7597263 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75972632020-11-09 Hierarchical Distribution Matching for Probabilistic Amplitude Shaping † Civelli, Stella Secondini, Marco Entropy (Basel) Article Probabilistic amplitude shaping—implemented through a distribution matcher (DM)—is an effective approach to enhance the performance and the flexibility of bandwidth-efficient coded modulations. Different DM structures have been proposed in the literature. Typically, both their performance and their complexity increase with the block length. In this work, we present a hierarchical DM (Hi-DM) approach based on the combination of several DMs of different possible types, which provides the good performance of long DMs with the low complexity of several short DMs. The DMs are organized in layers. Each upper-layer DM encodes information on a sequence of lower-layer DMs, which are used as “virtual symbols”. First, we describe the Hi-DM structure, its properties, and the encoding and decoding procedures. Then, we present three particular Hi-DM configurations, providing some practical design guidelines, and investigating their performance in terms of rate loss and energy loss. Finally, we compare the system performance obtained with the proposed Hi-DM structures and with their single-layer counterparts: a [Formula: see text] SNR gain is obtained by a two-layer Hi-DM based on constant composition DMs (CCDM) compared to a single-layer CCDM with same complexity; a [Formula: see text] gain and a significant complexity reduction are obtained by a Hi-DM based on minimum-energy lookup tables compared to a single-layer DM based on enumerative sphere shaping with same memory requirements. MDPI 2020-08-30 /pmc/articles/PMC7597263/ /pubmed/33286727 http://dx.doi.org/10.3390/e22090958 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Civelli, Stella Secondini, Marco Hierarchical Distribution Matching for Probabilistic Amplitude Shaping † |
title | Hierarchical Distribution Matching for Probabilistic Amplitude Shaping † |
title_full | Hierarchical Distribution Matching for Probabilistic Amplitude Shaping † |
title_fullStr | Hierarchical Distribution Matching for Probabilistic Amplitude Shaping † |
title_full_unstemmed | Hierarchical Distribution Matching for Probabilistic Amplitude Shaping † |
title_short | Hierarchical Distribution Matching for Probabilistic Amplitude Shaping † |
title_sort | hierarchical distribution matching for probabilistic amplitude shaping † |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7597263/ https://www.ncbi.nlm.nih.gov/pubmed/33286727 http://dx.doi.org/10.3390/e22090958 |
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