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In this paper, we propose two novel physical layer aware adaptive network coding and coded modulation schemes for time variant channels. The proposed schemes have been applied to different satellite communications scenarios with different…

Information Theory · Computer Science 2017-04-18 Ala Eddine Gharsellaoui , Samah A. M. Ghanem , Daniele Tarchi , Alessandro Vanelli-Coralli

This paper investigates low-latency streaming codes for a three-node relay network. The source transmits a sequence of messages (streaming messages) to the destination through the relay between them, where the first-hop channel from the…

Information Theory · Computer Science 2022-03-14 Silas L. Fong , Ashish Khisti , Baochun Li , Wai-Tian Tan , Xiaoqing Zhu , John Apostolopoulos

Polar codes are one of the most recent advancements in coding theory and they have attracted significant interest. While they are provably capacity achieving over various channels, they have seen limited practical applications.…

Information Theory · Computer Science 2016-11-17 Alexios Balatsoukas-Stimming , Georgios Karakonstantis , Andreas Burg

We give an information flow interpretation for multicasting using network coding. This generalizes the fluid model used to represent flows to a single receiver. Using the generalized model, we present a decentralized algorithm to minimize…

Information Theory · Computer Science 2007-07-13 Kapil Bhattad , Niranjan Ratnakar , Ralf Koetter , Krishna R. Narayanan

This work considers the problem of transmitting multiple compressible sources over a network at minimum cost. The aim is to find the optimal rates at which the sources should be compressed and the network flows using which they should be…

Information Theory · Computer Science 2009-08-13 Aditya Ramamoorthy

A novel fast recursive coding technique is proposed. It operates with only integer values not longer 8 bits and is multiplication free. Recursion the algorithm is based on indirectly provides rather effective coding of symbols for very…

Information Theory · Computer Science 2007-08-22 Nikolay Ponomarenko , Vladimir Lukin , Karen Egiazarian , Jaakko Astola , Boris Y Ryabko

We propose a novel soft-aided hard-decision decoding algorithm for general product-like codes. It achieves error correcting performance similar to that of a soft-decision turbo decoder for staircase and OFEC codes, while maintaining a low…

Information Theory · Computer Science 2024-05-01 Lukas Rapp , Sisi Miao , Laurent Schmalen

Quantum technologies have the potential to solve certain computationally hard problems with polynomial or super-polynomial speedups when compared to classical methods. Unfortunately, the unstable nature of quantum information makes it prone…

The advancement of deep learning has led to the development of neural decoders for low latency communications. However, neural decoders can be very complex which can lead to increased computation and latency. We consider iterative pruning…

Machine Learning · Computer Science 2022-11-17 Vikrant Malik , Rohan Ghosh , Mehul Motani

Motivated by the need for channel codes with low-complexity soft-decision decoding algorithms, we consider the recursive Plotkin concatenation of optimal low-rate and high-rate codes based on simplex codes and their duals. These component…

Information Theory · Computer Science 2025-10-14 Andreas Zunker , Marvin Rübenacke , Stephan ten Brink

A new algorithm for efficient exact maximum likelihood decoding of polar codes (which may be CRC augmented), transmitted over the binary erasure channel, is presented. The algorithm applies a matrix triangulation process on a sparse polar…

Information Theory · Computer Science 2021-06-29 Yonatan Urman , David Burshtein

A new class of folded subspace codes for noncoherent network coding is presented. The codes can correct insertions and deletions beyond the unique decoding radius for any code rate $R\in[0,1]$. An efficient interpolation-based decoding…

Information Theory · Computer Science 2015-04-22 Hannes Bartz , Vladimir Sidorenko

Deep learning-based image compression has made great progresses recently. However, many leading schemes use serial context-adaptive entropy model to improve the rate-distortion (R-D) performance, which is very slow. In addition, the…

Image and Video Processing · Electrical Eng. & Systems 2023-09-07 Haisheng Fu , Feng Liang , Jie Liang , Yongqiang Wang , Guohe Zhang , Jingning Han

It was estimated that the world produced $59 ZB$ ($5.9 \times 10^{13} GB$) of data in 2020, resulting in the enormous costs of both data storage and transmission. Fortunately, recent advances in deep generative models have spearheaded a new…

Machine Learning · Computer Science 2021-11-02 Shifeng Zhang , Ning Kang , Tom Ryder , Zhenguo Li

This paper seeks to combine dictionary learning and hierarchical image representation in a principled way. To make dictionary atoms capturing additional information from extended receptive fields and attain improved descriptive capacity, we…

Computer Vision and Pattern Recognition · Computer Science 2019-11-11 Tong Zhang , Fatih Porikli

In this paper, we present the block Markov superposition transmission of BCH (BMST-BCH) codes, which can be constructed to obtain a very low error floor. To reduce the implementation complexity, we design a low complexity iterative…

Information Theory · Computer Science 2017-08-22 Suihua Cai , Nina Lin , Xiao Ma

In this article we focus on the problem of channel decoding in presence of a-priori information. In particular, assuming that the a-priori information reliability is not perfectly estimated at the receiver, we derive a novel analytical…

Information Theory · Computer Science 2007-11-14 Andrea Abrardo

Point clouds obtained from capture devices or 3D reconstruction techniques are often noisy and interfere with downstream tasks. The paper aims to recover the underlying surface of noisy point clouds. We design a novel model, NoiseTrans,…

Computer Vision and Pattern Recognition · Computer Science 2023-04-25 Guangzhe Hou , Guihe Qin , Minghui Sun , Yanhua Liang , Jie Yan , Zhonghan Zhang

Partial Unit Memory (PUM) codes are a special class of convolutional codes, which are often constructed by means of block codes. Decoding of PUM codes may take advantage of existing decoders for the block code. The Dettmar--Sorger algorithm…

Information Theory · Computer Science 2012-02-09 Antonia Wachter-Zeh , Markus Stinner , Martin Bossert

Coded caching is a recently proposed technique that achieves significant performance gains for cache networks compared to uncoded caching schemes. However, this substantial coding gain is attained at the cost of large delivery delay, which…

Information Theory · Computer Science 2016-11-15 Urs Niesen , Mohammad Ali Maddah-Ali