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20192026
most citedA Revisit to Ordered Statistics Decoding: Distance Distribution and Decoding Rules

67 citations · 73 across the 22 of their papers we have counts for

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17 papers · 1 filter

cs.IT2026

Semantic Error Control Coding with Foundation Models for Future Communications

Chentao Yue, Gaoyang Pang, Branka Vucetic +1

Classical channel decoding typically treats all information sequences as equally likely and relies primarily on the channel observations and code structure, without exploiting stat…

cs.IT2026

Semantic-Aided Iterative Decoding for Uplink Non-Orthogonal Transmission

Wenjing Wei, Chentao Yue, Branka Vucetic +1

This paper proposes semantic-aided iterative decoding (Sem-IR) for uplink non-orthogonal transmission of a shared natural-language source. K users each hold one segment of a common…

cs.IT2026

Semantic Ordered Statistics Decoding

Chentao Yue, Branka Vucetic, Yonghui Li

We propose a Semantic Ordered Statistics Decoder (sem-OSD), a soft decoder for short linear block codes carrying byte-streamed sources such as natural-language text. Sem-OSD inject…

cs.IT2026

Semantic Error Correction and Decoding for Short Block Codes

Jiafu Hao, Chentao Yue, Wanchun Liu +2

This paper presents a semantic-enhanced receiver framework for transmitting natural language sentences over noisy wireless channels using multiple short block codes. After ASCII en…

cs.IT2026

LLM-Viterbi: Semantic-Aware Decoding for Convolutional Codes

Zhengtong Li, Chentao Yue, Jiafu Hao +2

Traditional wireless communications rely solely on bit-level channel coding for error correction, without exploiting the inherent linguistic structure of the data source. This pape…

cs.IT2025

Policy-Guided MCTS for near Maximum-Likelihood Decoding of Short Codes

Y. Tian, C. Yue, P. Cheng +3

In this paper, we propose a policy-guided Monte Carlo Tree Search (MCTS) decoder that achieves near maximum-likelihood decoding (MLD) performance for short block codes. The MCTS de…

cs.IT2025

Optimal Linear MAP Decoding of Convolutional Codes

Yonghui Li, Chentao Yue, Branka Vucetic

In this paper, we propose a linear representation of BCJR maximum a posteriori probability (MAP) decoding of a rate 1/2 convolutional code (CC), referred to as the linear MAP decod…

cs.IT2024

The Guesswork of Ordered Statistics Decoding: Guesswork Complexity and Decoder Design

Chentao Yue, Changyang She, Branka Vucetic +1

This paper investigates guesswork over ordered statistics and formulates the achievable guesswork complexity of ordered statistics decoding (OSD) in binary additive white Gaussian…

cs.IT2023

Efficient Near Maximum-Likelihood Reliability-Based Decoding for Short LDPC Codes

Weiyang Zhang, Chentao Yue, Yonghui Li +1

In this paper, we propose an efficient decoding algorithm for short low-density parity check (LDPC) codes by carefully combining the belief propagation (BP) decoding and order stat…

cs.IT2022

A Scalable Graph Neural Network Decoder for Short Block Codes

Kou Tian, Chentao Yue, Changyang She +2

In this work, we propose a novel decoding algorithm for short block codes based on an edge-weighted graph neural network (EW-GNN). The EW-GNN decoder operates on the Tanner graph w…

cs.IT2022

Ordered-Statistics Decoding with Adaptive Gaussian Elimination Reduction for Short Codes

Chentao Yue, Mahyar Shirvanimoghaddam, Branka Vucetic +1

In this paper, we propose an efficient ordered-statistics decoding (OSD) algorithm with an adaptive Gaussian elimination (GE) reduction technique. The proposed decoder utilizes two…

cs.IT2022

Efficient Decoders for Short Block Length Codes in 6G URLLC

Chentao Yue, Vera Miloslavskaya, Mahyar Shirvanimoghaddam +2

This paper reviews the potential channel decoding techniques for ultra-reliable low-latency communications (URLLC). URLLC is renowned for its stringent requirements including ultra…

cs.IT2021

Density Evolution Analysis of the Iterative Joint Ordered-Statistics Decoding for NOMA

Chentao Yue, Mahyar Shirvanimoghaddam, Alva Kosasih +5

In this paper, we develop a density evolution (DE) framework for analyzing the iterative joint decoding (JD) for non-orthogonal multiple access (NOMA) systems, where the ordered-st…

cs.IT2021

NOMA Joint Decoding based on Soft-Output Ordered-Statistics Decoder for Short Block Codes

Chentao Yue, Alva Kosasih, Mahyar Shirvanimoghaddam +5

In this paper, we design the joint decoding (JD) of non-orthogonal multiple access (NOMA) systems employing short block length codes. We first proposed a low-complexity soft-output…

cs.IT2021★ 2 cited

Linear-Equation Ordered-Statistics Decoding

Chentao Yue, Mahyar Shirvanimoghaddam, Giyoon Park +3

In this paper, we propose a new linear-equation ordered-statistics decoding (LE-OSD). Unlike the OSD, LE-OSD uses high reliable parity bits rather than information bits to recover…

cs.IT2020★ 67 cited

A Revisit to Ordered Statistics Decoding: Distance Distribution and Decoding Rules

Chentao Yue, Mahyar Shirvanimoghaddam, Branka Vucetic +1

This paper revisits the ordered statistics decoding (OSD). It provides a comprehensive analysis of the OSD algorithm by characterizing the statistical properties, evolution and the…

cs.IT2019★ 1 cited

Segmentation-Discarding Ordered-Statistic Decoding for Linear Block Codes

Chentao Yue, Mahyar Shirvanimoghaddam, Yonghui Li +1

In this paper, we propose an efficient reliability based segmentation-discarding decoding (SDD) algorithm for short block-length codes. A novel segmentation-discarding technique is…