We introduce a novel universal soft-decision decoding algorithm for binary block codes called ordered reliability direct error pattern testing (ORDEPT). Our results, obtained for a variety of popular short high-rate codes, demonstrate that ORDEPT outperforms state-of-the-art decoding algorithms of comparable complexity such as ordered reliability bits guessing random additive noise decoding (ORBGRAND) in terms of the decoding error probability and latency. The improvements carry on to the iterative decoding of product codes and convolutional product-like codes, where we present a new adaptive decoding algorithm and demonstrate the ability of ORDEPT to efficiently find multiple candidate codewords to produce soft output
In this dissertation, advanced channel decoding techniques based on bit-level soft information are s...
In this paper, a novel simplified statistical approach to evaluate the error performance bound of Or...
The A* algorithm finds the path in a finite depth binary tree that optimizes a function. Here, it is...
Modern applications are driving demand for ultra- reliable low-latency communications, rekindling i...
Guessing Random Additive Noise Decoding (GRAND) is a universal decoding algorithm that can be used t...
International audienceIn this paper we study the sensibility of the recently proposed Arranged List ...
Abstract-This paper presents a novel approach to soft decision decoding for binary linear block code...
Thesis (Ph. D.)--University of Hawaii at Manoa, 1994.Includes bibliographical references (leaves 177...
International audienceIn this paper we propose the Arranged List of the Most a priori Likely Tests (...
131 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2004.When channel reliability info...
In this paper we consider Ordered Statistics Decoding and we discuss some ideas aiming to reduce its...
In this work, we investigate guessing random additive noise decoding (GRAND) with quantized soft inp...
Products codes (PCs) are conventionally decoded with efficient iterative bounded-distance decoding (...
In this correspondence, we consider the decoding of binary block codes over the additive white Gauss...
International audiencePresented is a soft-decision decoding algorithm for a particular class of rate...
In this dissertation, advanced channel decoding techniques based on bit-level soft information are s...
In this paper, a novel simplified statistical approach to evaluate the error performance bound of Or...
The A* algorithm finds the path in a finite depth binary tree that optimizes a function. Here, it is...
Modern applications are driving demand for ultra- reliable low-latency communications, rekindling i...
Guessing Random Additive Noise Decoding (GRAND) is a universal decoding algorithm that can be used t...
International audienceIn this paper we study the sensibility of the recently proposed Arranged List ...
Abstract-This paper presents a novel approach to soft decision decoding for binary linear block code...
Thesis (Ph. D.)--University of Hawaii at Manoa, 1994.Includes bibliographical references (leaves 177...
International audienceIn this paper we propose the Arranged List of the Most a priori Likely Tests (...
131 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2004.When channel reliability info...
In this paper we consider Ordered Statistics Decoding and we discuss some ideas aiming to reduce its...
In this work, we investigate guessing random additive noise decoding (GRAND) with quantized soft inp...
Products codes (PCs) are conventionally decoded with efficient iterative bounded-distance decoding (...
In this correspondence, we consider the decoding of binary block codes over the additive white Gauss...
International audiencePresented is a soft-decision decoding algorithm for a particular class of rate...
In this dissertation, advanced channel decoding techniques based on bit-level soft information are s...
In this paper, a novel simplified statistical approach to evaluate the error performance bound of Or...
The A* algorithm finds the path in a finite depth binary tree that optimizes a function. Here, it is...