Low-Density Parity-Check Codes and Their Rateless Relatives Nicholas Bonello, Sheng Chen, and Lajos Hanzo
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Tm Synchronization and Channel Coding—Summary of Concept and Rationale
Report Concerning Space Data System Standards TM SYNCHRONIZATION AND CHANNEL CODING— SUMMARY OF CONCEPT AND RATIONALE INFORMATIONAL REPORT CCSDS 130.1-G-3 GREEN BOOK June 2020 Report Concerning Space Data System Standards TM SYNCHRONIZATION AND CHANNEL CODING— SUMMARY OF CONCEPT AND RATIONALE INFORMATIONAL REPORT CCSDS 130.1-G-3 GREEN BOOK June 2020 TM SYNCHRONIZATION AND CHANNEL CODING—SUMMARY OF CONCEPT AND RATIONALE AUTHORITY Issue: Informational Report, Issue 3 Date: June 2020 Location: Washington, DC, USA This document has been approved for publication by the Management Council of the Consultative Committee for Space Data Systems (CCSDS) and reflects the consensus of technical panel experts from CCSDS Member Agencies. The procedure for review and authorization of CCSDS Reports is detailed in Organization and Processes for the Consultative Committee for Space Data Systems (CCSDS A02.1-Y-4). This document is published and maintained by: CCSDS Secretariat National Aeronautics and Space Administration Washington, DC, USA Email: [email protected] CCSDS 130.1-G-3 Page i June 2020 TM SYNCHRONIZATION AND CHANNEL CODING—SUMMARY OF CONCEPT AND RATIONALE FOREWORD This document is a CCSDS Report that contains background and explanatory material to support the CCSDS Recommended Standard, TM Synchronization and Channel Coding (reference [3]). Through the process of normal evolution, it is expected that expansion, deletion, or modification of this document may occur. This Report is therefore subject to CCSDS document management and change control procedures, which are defined in Organization and Processes for the Consultative Committee for Space Data Systems (CCSDS A02.1-Y-4). Current versions of CCSDS documents are maintained at the CCSDS Web site: http://www.ccsds.org/ Questions relating to the contents or status of this document should be sent to the CCSDS Secretariat at the email address indicated on page i. -
MHOMS: High Speed ACM Modem for Satellite Applications1
MHOMS : high speed ACM modem for satellite applications Sergio Benedetto, Claude Berrou, Catherine Douillard, Roberto Garello, Domenico Giancristofaro, Alberto Ginesi, Luca Giugno, Marco Luise, G. Montorsi To cite this version: Sergio Benedetto, Claude Berrou, Catherine Douillard, Roberto Garello, Domenico Giancristofaro, et al.. MHOMS : high speed ACM modem for satellite applications. IEEE Wireless Communications, In- stitute of Electrical and Electronics Engineers, 2005, 12 (2), pp.66 - 77. 10.1109/MWC.2005.1421930. hal-02137104 HAL Id: hal-02137104 https://hal.archives-ouvertes.fr/hal-02137104 Submitted on 22 May 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. MHOMS: High Speed ACM Modem for Satellite Applications1 S. Benedetto(3), C. Berrou(5), C. Douillard(5), R. Garello(3), D. Giancristofaro(1), A. Ginesi(2), L. Giugno(4), M. Luise(4), G. Montorsi(3), (1) Alenia Spazio (2) European Space Agency (3) Politecnico di Torino (4) Università di Pisa (5) ENST Bretagne Table of Contents 1 Introduction...................................................................................................................................................................... -
Convolutional Codes in Vss
CONVOLUTIONAL CODES IN VSS . .. By: Dr. Kurt R. Matis Director of Systems Research SIMULATION OF CONVOLUTIONAL CODES IN VSS This document describes the modeling and simulation of short constraint- length convolutional codes used in conjunction with Viterbi decoding in the Visual System Simulator (VSS). After a brief review of the history and application of convolutional codes, a detailed description of VSS models for encoding/decoding of these codes is presented. Step-by-step examples illustrate how to construct simulations and analyze results. Convolutional Code Basics This note begins with some background information on the use of convolutional codes. The development of convolutional codes is discussed along with a history of important applications. This information is meant to provide a perspective on the selection of the convolutional code models that are provided in VSS. Transmission efficiency and reliability can be improved by encoding information digits in a way that creates an interdependence between symbols which are transmitted over a channel. At the receiving end, the interdependence can be exploited to detect or even correct transmission errors, provided erroneous symbols are not received too frequently. Such coding is called error-control coding and is shown in the configuration of Figure 1. Received Source Encoded Symbols Decoded Symbols Symbols ˆ Symbols {bk } {ai} Channel {bk} Transmitter s(t) Channel r(t) Receiver Channel {âi} Encoder Decoder {rk} Figure 1. System Employing Error-Control Coding Visual System Simulator 1 CONVOLUTIONAL CODES IN VSS Simulation of Convolutional Codes in VSS Encoders for error control are usually called channel encoders to differentiate them from various encoders used for other purposes within digital communication systems. -
Raptor Codes Amin Shokrollahi, Senior Member, IEEE
IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 52, NO. 6, JUNE 2006 2551 Raptor Codes Amin Shokrollahi, Senior Member, IEEE Abstract—LT-codes are a new class of codes introduced by Luby such as poor wireless or satellite links. Moreover, ack-based for the purpose of scalable and fault-tolerant distribution of data protocols such as TCP perform poorly when the distance be- over computer networks. In this paper, we introduce Raptor codes, tween the sender and the receiver is long, since large distances an extension of LT-codes with linear time encoding and decoding. We will exhibit a class of universal Raptor codes: for a given in- lead to idle times during which the sender waits for an acknowl- teger and any real , Raptor codes in this class produce a edgment and cannot send data. potentially infinite stream of symbols such that any subset of sym- For these reasons, other transmission solutions have been pro- bols of size is sufficient to recover the original sym- posed. One class of such solutions is based on coding. The orig- bols with high probability. Each output symbol is generated using inal data is encoded using some linear erasure correcting code. operations, and the original symbols are recovered from the collected ones with operations. If during the transmission some part of the data is lost, then it We will also introduce novel techniques for the analysis of the is possible to recover the lost data using erasure correcting al- error probability of the decoder for finite length Raptor codes. gorithms. For applications it is crucial that the codes used are Moreover, we will introduce and analyze systematic versions of capable of correcting as many erasures as possible, and it is Raptor codes, i.e., versions in which the first output elements of also crucial that the encoding and decoding algorithms for these the coding system coincide with the original elements. -
CRC-Assisted Error Correction in a Convolutionally Coded System Renqiu Wang, Member, IEEE, Wanlun Zhao, Member, IEEE, and Georgios B
IEEE TRANSACTIONS ON COMMUNICATIONS, VOL. 56, NO. 11, NOVEMBER 2008 1807 CRC-Assisted Error Correction in a Convolutionally Coded System Renqiu Wang, Member, IEEE, Wanlun Zhao, Member, IEEE, and Georgios B. Giannakis, Fellow, IEEE Abstract—In communication systems employing a serially When the signal to noise ratio (SNR) is relatively high, only a concatenated cyclic redundancy check (CRC) code along with small number of errors are typically present in an erroneously a convolutional code (CC), erroneous packets after CC decoding decoded packet. Instead of discarding the entire packet, the are usually discarded. The list Viterbi algorithm (LVA) and the iterative Viterbi algorithm (IVA) are two existing approaches theme is this paper is to possibly recover it by utilizing jointly capable of recovering erroneously decoded packets. We here ECC and CRC. employ a soft decoding algorithm for CC decoding, and introduce We will study a system with serially concatenated CRC and several schemes to identify error patterns using the posterior CC (CRC-CC). Being a special case of conventional serially information from the CC soft decoding module. The resultant iterative decoding-detecting (IDD) algorithm improves error concatenated codes (CSCC) [1], CRC-CC has been widely performance by iteratively updating the extrinsic information applied in wireless communications, for example, in an IS-95 based on the CRC parity check matrix. Assuming errors only system. Various approaches are available to recover erroneous happen in unreliable bits characterized by small absolute values packets following the Viterbi decoding stage. One of them is of the log-likelihood ratio (LLR), we also develop a partial IDD based on the list Viterbi algorithm (LVA), which produces a (P-IDD) alternative which exhibits comparable performance to IDD by updating only a subset of unreliable bits. -
Tm Synchronization and Channel Coding
Recommendation for Space Data System Standards TM SYNCHRONIZATION AND CHANNEL CODING RECOMMENDED STANDARD CCSDS 131.0-B-3 BLUE BOOK September 2017 Recommendation for Space Data System Standards TM SYNCHRONIZATION AND CHANNEL CODING RECOMMENDED STANDARD CCSDS 131.0-B-3 BLUE BOOK September 2017 CCSDS RECOMMENDED STANDARD FOR TM SYNCHRONIZATION AND CHANNEL CODING AUTHORITY Issue: Recommended Standard, Issue 3 Date: September 2017 Location: Washington, DC, USA This document has been approved for publication by the Management Council of the Consultative Committee for Space Data Systems (CCSDS) and represents the consensus technical agreement of the participating CCSDS Member Agencies. The procedure for review and authorization of CCSDS documents is detailed in Organization and Processes for the Consultative Committee for Space Data Systems (CCSDS A02.1-Y-4), and the record of Agency participation in the authorization of this document can be obtained from the CCSDS Secretariat at the e-mail address below. This document is published and maintained by: CCSDS Secretariat National Aeronautics and Space Administration Washington, DC, USA E-mail: [email protected] CCSDS 131.0-B-3 Page i September 2017 CCSDS RECOMMENDED STANDARD FOR TM SYNCHRONIZATION AND CHANNEL CODING STATEMENT OF INTENT The Consultative Committee for Space Data Systems (CCSDS) is an organization officially established by the management of its members. The Committee meets periodically to address data systems problems that are common to all participants, and to formulate sound technical solutions to these problems. Inasmuch as participation in the CCSDS is completely voluntary, the results of Committee actions are termed Recommended Standards and are not considered binding on any Agency. -
Skew Convolutional Codes
entropy Article Skew Convolutional Codes Vladimir Sidorenko 1,* , Wenhui Li 2, Onur Günlü 3 and Gerhard Kramer 1 1 Institute for Communications Engineering, Technical University of Munich, 80333 München, Germany; [email protected] 2 Skolkovo Institute of Science and Technology, 143026 Moscow, Russia; [email protected] 3 Information Theory and Applications Chair, Technical University of Berlin, 10623 Berlin, Germany; [email protected] * Correspondence: [email protected] Received: 30 October 2020; Accepted: 30 November 2020; Published: 2 December 2020 Abstract: A new class of convolutional codes, called skew convolutional codes, that extends the class of classical fixed convolutional codes, is proposed. Skew convolutional codes can be represented as periodic time-varying convolutional codes but have a description as compact as fixed convolutional codes. Designs of generator and parity check matrices, encoders, and code trellises for skew convolutional codes and their duals are shown. For memoryless channels, one can apply Viterbi or BCJR decoding algorithms, or a dualized BCJR algorithm, to decode skew convolutional codes. Keywords: convolutional codes; skew polynomials; time-varying codes; dual codes; trellises 1. Introduction Convolutional codes were introduced by Elias in 1955 [1]. With the discovery that convolutional codes can be decoded with Fano sequential decoding [2], Massey threshold decoding [3], and, above all, Viterbi decoding [4], they became quite widespread in practice. Convolutional codes are still widely used in telecommunications, e.g., in Turbo codes [5] and in the WiFi IEEE 802.11 standard [6], in cryptography [7], etc. The most common are binary convolutional codes; however, communication with higher orders of modulation [8] or streaming of data [9] require non-binary convolutional codes. -
Error-Correcting Codes: Application of Convolutional Codes to Video Streaming
Introduction to Error-correcting codes Two challenges that recently emerged Block codes vs convolutional codes Error-Correcting codes: Application of convolutional codes to Video Streaming Diego Napp Department of Mathematics, Universidad of Aveiro, Portugal July 22, 2016 Introduction to Error-correcting codes Two challenges that recently emerged Block codes vs convolutional codes Overview Introduction to Error-correcting codes Two challenges that recently emerged Block codes vs convolutional codes • Bits get corrupted, 0 ! 1 or 1 ! 0, but rarely. What happens when we store/send information and errors occur? can we detect them? correct? Introduction to Error-correcting codes Two challenges that recently emerged Block codes vs convolutional codes Error Correcting Codes Basic Problem: • want to store bits on magnetic storage device • or send a message (sequence of zeros/ones) What happens when we store/send information and errors occur? can we detect them? correct? Introduction to Error-correcting codes Two challenges that recently emerged Block codes vs convolutional codes Error Correcting Codes Basic Problem: • want to store bits on magnetic storage device • or send a message (sequence of zeros/ones) • Bits get corrupted, 0 ! 1 or 1 ! 0, but rarely. can we detect them? correct? Introduction to Error-correcting codes Two challenges that recently emerged Block codes vs convolutional codes Error Correcting Codes Basic Problem: • want to store bits on magnetic storage device • or send a message (sequence of zeros/ones) • Bits get corrupted, 0 ! 1 or 1 ! 0, but rarely. What happens when we store/send information and errors occur? Introduction to Error-correcting codes Two challenges that recently emerged Block codes vs convolutional codes Error Correcting Codes Basic Problem: • want to store bits on magnetic storage device • or send a message (sequence of zeros/ones) • Bits get corrupted, 0 ! 1 or 1 ! 0, but rarely. -
A Digital Fountain Retrospective
A Digital Fountain Retrospective John W. Byers Michael Luby Michael Mitzenmacher Boston University ICSI, Berkeley, CA Harvard University This article is an editorial note submitted to CCR. It has NOT been peer reviewed. The authors take full responsibility for this article’s technical content. Comments can be posted through CCR Online. ABSTRACT decoding can not occur and the receiver falls back to retransmission We introduced the concept of a digital fountain as a scalable approach based protocols. to reliable multicast, realized with fast and practical erasure codes, More fundamentally, in a multicast setting where concurrent in a paper published in ACM SIGCOMM ’98. This invited editorial, receivers experience different packet loss patterns, efficiently or- on the occasion of the 50th anniversary of the SIG, reflects on the chestrating transmissions from a fixed amount of encoding (see, trajectory of work leading up to our approach, and the numerous e.g., [31]), becomes unwieldy at best, and runs into significant scal- developments in the field in the subsequent 21 years. We discuss ing issues as the number of receivers grows. advances in rateless codes, efficient implementations, applications The research described in [6], [7] (awarded the ACM SIGCOMM of digital fountains in distributed storage systems, and connections Test of Time award) introduced the concept of an erasure code to invertible Bloom lookup tables. without a predetermined code rate. Instead, as much encoded data as needed could be generated efficiently from source data on the CCS CONCEPTS fly. Such an erasure code was called a digital fountain in [6], [7], which also described a number of compelling use cases. -
Raptor Codes Full Text Available At
Full text available at: http://dx.doi.org/10.1561/0100000060 Raptor Codes Full text available at: http://dx.doi.org/10.1561/0100000060 Raptor Codes Amin Shokrollahi EPFL Station 14 Lausanne 1015 Switzerland amin.shokrollahi@epfl.ch Michael Luby Qualcomm, Inc. 3195 Kifer Road Santa Clara, CA 95051 USA [email protected] Boston { Delft Full text available at: http://dx.doi.org/10.1561/0100000060 Foundations and Trends R in Communications and Information Theory Published, sold and distributed by: now Publishers Inc. PO Box 1024 Hanover, MA 02339 USA Tel. +1-781-985-4510 www.nowpublishers.com [email protected] Outside North America: now Publishers Inc. PO Box 179 2600 AD Delft The Netherlands Tel. +31-6-51115274 The preferred citation for this publication is A. Shokrollahi and M. Luby, Rap- tor Codes, Foundations and Trends R in Communications and Information Theory, vol 6, nos 3{4, pp 213{322, 2009 ISBN: 978-1-60198-446-3 c 2011 A. Shokrollahi and M. Luby All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, mechanical, photocopying, recording or otherwise, without prior written permission of the publishers. Photocopying. In the USA: This journal is registered at the Copyright Clearance Cen- ter, Inc., 222 Rosewood Drive, Danvers, MA 01923. Authorization to photocopy items for internal or personal use, or the internal or personal use of specific clients, is granted by now Publishers Inc for users registered with the Copyright Clearance Center (CCC). The `services' for users can be found on the internet at: www.copyright.com For those organizations that have been granted a photocopy license, a separate system of payment has been arranged. -
AN INTRODUCTION to ERROR CORRECTING CODES Part 1 Jack Keil Wolf ECE 154C
AN INTRODUCTION TO ERROR CORRECTING CODES Part 1 Jack Keil Wolf ECE 154C Spring 2008 Noisy Communications • Noise in a communications channel can cause errors in the transmission of binary digits. • Transmit: 1 1 0 0 1 0 1 0 1 1 1 0 0 0 0 1 0 … • Receive: 1 1 0 1 1 0 1 0 001 0 0 0 0 1 0 … • For some types of information, errors can be detected and corrected but not in others. Example: Transmit: Come to my house at 17:25 … Receive: Come tc my houzx at 14:25 … Making Digits Redundant • In binary error correcting codes, only certain binary sequences (called code words) are transmitted. • This is similar to having a dictionary of allowable words. • After transmission over a noisy channel, we can check to see if the received binary sequence is in the dictionary of code words and if not, choose the codeword most similar to what was received. NATURE’S ERROR CONTROL CODE • Nature’s code is a mapping of RNA sequences to proteins. • “RNA” consists of four “symbols": A, U, G, and C. “Proteins” consists of 20 “symbols": the amino acids. • The genetic code is a code in which three nucleotides in RNA specify one amino acid in protein. NATURE’S ERROR CONTROL DECODING TABLE Sometimes one or more of the RNA symbols Is changed. Hopefully, the AUG starts resultant triplet codon. still decodes to the same protein. RNA-Amino Acid Coding OUTLINE • Types of Error Correction Codes • Block Codes: – Example: (7,4) Hamming Codes – General Theory of Binary Group Codes – Low Density Parity Check (LDPC) Codes – Reed Solomon (RS) Codes • Convolutional Codes & Viterbi Decoding – Example: Rate ½ 4 State Code – General Description of Convolutional Codes – Punctured Codes – Decoding and the Viterbi Algorithm – Turbo codes BINARY ERROR CORRECTING CODES: (ECC) • 2k equally likely messages can be represented by k binary digits. -
ETR 192 TECHNICAL July 1995 REPORT
ETSI ETR 192 TECHNICAL July 1995 REPORT Source: ETSI TC-SES Reference: DTR/SES-04014 ICS: 33.060, 33.060.20 Key words: broadcasting, contribution, earth station, radio, satellite, TV Satellite Earth Stations and Systems (SES); Modulation and channel coding of 34,368 Mbit/s and 44,736 Mbit/s digital television contribution links via satellite ETSI European Telecommunications Standards Institute ETSI Secretariat Postal address: F-06921 Sophia Antipolis CEDEX - FRANCE Office address: 650 Route des Lucioles - Sophia Antipolis - Valbonne - FRANCE X.400: c=fr, a=atlas, p=etsi, s=secretariat - Internet: [email protected] Tel.: +33 92 94 42 00 - Fax: +33 93 65 47 16 Copyright Notification: No part may be reproduced except as authorized by written permission. The copyright and the foregoing restriction extend to reproduction in all media. New presentation - see History box © European Telecommunications Standards Institute 1995. All rights reserved. Page 2 ETR 192: July 1995 Whilst every care has been taken in the preparation and publication of this document, errors in content, typographical or otherwise, may occur. If you have comments concerning its accuracy, please write to "ETSI Editing and Committee Support Dept." at the address shown on the title page. Page 3 ETR 192: July 1995 Contents Foreword .......................................................................................................................................................5 Introduction....................................................................................................................................................5