Reed-Solomon Encoding and Decoding
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Recommendation Itu-R Bt.2016*
Recommendation ITU-R BT.2016 (04/2012) Error-correction, data framing, modulation and emission methods for terrestrial multimedia broadcasting for mobile reception using handheld receivers in VHF/UHF bands BT Series Broadcasting service (television) ii Rec. ITU-R BT.2016 Foreword The role of the Radiocommunication Sector is to ensure the rational, equitable, efficient and economical use of the radio-frequency spectrum by all radiocommunication services, including satellite services, and carry out studies without limit of frequency range on the basis of which Recommendations are adopted. The regulatory and policy functions of the Radiocommunication Sector are performed by World and Regional Radiocommunication Conferences and Radiocommunication Assemblies supported by Study Groups. Policy on Intellectual Property Right (IPR) ITU-R policy on IPR is described in the Common Patent Policy for ITU-T/ITU-R/ISO/IEC referenced in Annex 1 of Resolution ITU-R 1. Forms to be used for the submission of patent statements and licensing declarations by patent holders are available from http://www.itu.int/ITU-R/go/patents/en where the Guidelines for Implementation of the Common Patent Policy for ITU-T/ITU-R/ISO/IEC and the ITU-R patent information database can also be found. Series of ITU-R Recommendations (Also available online at http://www.itu.int/publ/R-REC/en) Series Title BO Satellite delivery BR Recording for production, archival and play-out; film for television BS Broadcasting service (sound) BT Broadcasting service (television) F Fixed service M Mobile, radiodetermination, amateur and related satellite services P Radiowave propagation RA Radio astronomy RS Remote sensing systems S Fixed-satellite service SA Space applications and meteorology SF Frequency sharing and coordination between fixed-satellite and fixed service systems SM Spectrum management SNG Satellite news gathering TF Time signals and frequency standards emissions V Vocabulary and related subjects Note: This ITU-R Recommendation was approved in English under the procedure detailed in Resolution ITU-R 1. -
ACRONYMS and ABBREVIATIONS BLUETOOTH SPECIFICATION Version 1.1 Page 914 of 1084
Appendix III ACRONYMS AND ABBREVIATIONS BLUETOOTH SPECIFICATION Version 1.1 page 914 of 1084 Appendix III - Acronyms 914 22 February 2001 BLUETOOTH SPECIFICATION Version 1.1 page 915 of 1084 Appendix III - Acronyms List of Acronyms and Abbreviations Acronym or Writing out in full Which means abbreviation ACK Acknowledge ACL link Asynchronous Connection-Less Provides a packet-switched con- link nection.(Master to any slave) ACO Authenticated Ciphering Offset AM_ADDR Active Member Address AR_ADDR Access Request Address ARQ Automatic Repeat reQuest B BB BaseBand BCH Bose, Chaudhuri & Hocquenghem Type of code The persons who discovered these codes in 1959 (H) and 1960 (B&C) BD_ADDR Bluetooth Device Address BER Bit Error Rate BT Bandwidth Time BT Bluetooth C CAC Channel Access Code CC Call Control CL Connectionless CODEC COder DECoder COF Ciphering Offset CRC Cyclic Redundancy Check CVSD Continuous Variable Slope Delta Modulation D DAC Device Access Code DCE Data Communication Equipment 22 February 2001 915 BLUETOOTH SPECIFICATION Version 1.1 page 916 of 1084 Appendix III - Acronyms Acronym or Writing out in full Which means abbreviation DCE Data Circuit-Terminating Equip- In serial communications, DCE ment refers to a device between the communication endpoints whose sole task is to facilitate the commu- nications process; typically a modem DCI Default Check Initialization DH Data-High Rate Data packet type for high rate data DIAC Dedicated Inquiry Access Code DM Data - Medium Rate Data packet type for medium rate data DTE Data Terminal Equipment In serial communications, DTE refers to a device at the endpoint of the communications path; typi- cally a computer or terminal. -
Implementation and Evaluation of Polar Codes in 5G
Implementation and evaluation of Polar Codes in 5G Implementation och evaluering av Polar Codes för 5G Tobias Rosenqvist Joël Sloof Faculty of Health, Science and Technology Computer Science 15 hp Supervisor: Stefan Alfredsson Examiner: Kerstin Andersson Date: 2019-06-12 Serial number: N/A Implementation and evaluation of Polar Codes in 5G Tobias Rosenqvist, Joël Sloof © 2019 The author(s) and Karlstad University This report is submitted in partial fulfillment of the requirements for the Bachelor’s degree in Computer Science. All material in this report which is not our own work has been identified and no material is included for which a degree has previously been conferred. Tobias Rosenqvist Joël Sloof Approved, Date of defense Advisor: Stefan Alfredsson Examiner: Kerstin Andersson iii Abstract In today’s society the ability to communicate with one another has grown, were a lot of focus is aimed towards speed in the telecommunication industry. For transmissions to become even faster, there are many ways to enhance transmission speeds of which error correction is one. Padding messages such that they are protected from noise, while using as few bits as possible and ensuring safe transmit is handled by error correction codes. Short codes with low complexity is a solution to faster transmission speeds. An error correction code which has gained a lot of attention since its first appearance in 2009 is Polar Codes. Polar Codes was chosen as the 3GPP standard for 5G control channel. The goal of the thesis is to develop and implement Polar Codes and rate matching according to the 3GPP standard 38.212. -
Applicability of the Julia Programming Language to Forward Error-Correction Coding in Digital Communications Systems
Applicability of the Julia Programming Language to Forward Error-Correction Coding in Digital Communications Systems A project presented to Department of Computer and Information Sciences State University of New York Polytechnic Institute At Utica/Rome Utica, New York In partial fulfillment Of the requirements of the Master of Science Degree by Ryan Quinn May 2018 Declaration I declare that this project is my own work and has not been submitted in any form for another degree of diploma at any university of other institute of tertiary education. Information derived from published and unpublished work of others has been acknowledged in the text and a list of references given. _ Ryan Quinn 2 | P a g e SUNY POLYTECHNIC INSTITUTE DEPARTMENT OF COMPUTER AND INFORMATION SCIENCES Approved and recommended for acceptance as a project in partial fulfillment of the requirements for the degree of Master of Science in computer and information science _ DATE _ Dr. Bruno R. Andriamanalimanana Advisor _ Dr. Saumendra Sengupta _ Dr. Scott Spetka 3 | P a g e 1 ABSTRACT Traditionally SDR has been implemented in C and C++ for execution speed and processor efficiency. Interpreted and high-level languages were considered too slow to handle the challenges of digital signal processing (DSP). The Julia programming language is a new language developed for scientific and mathematical purposes that is supposed to write like Python or MATLAB and execute like C or FORTRAN. Given the touted strengths of the Julia language, it bore investigating as to whether it was suitable for DSP. This project specifically addresses the applicability of Julia to forward error correction (FEC), a highly mathematical topic to which Julia should be well suited. -
16.548 Notes 15: Concatenated Codes, Turbo Codes and Iterative Processing Outline
16.548 Notes 15: Concatenated Codes, Turbo Codes and Iterative Processing Outline ! Introduction " Pushing the Bounds on Channel Capacity " Theory of Iterative Decoding " Recursive Convolutional Coding " Theory of Concatenated codes ! Turbo codes " Encoding " Decoding " Performance analysis " Applications ! Other applications of iterative processing " Joint equalization/FEC " Joint multiuser detection/FEC Shannon Capacity Theorem Capacity as a function of Code rate Motivation: Performance of Turbo Codes. Theoretical Limit! ! Comparison: " Rate 1/2 Codes. " K=5 turbo code. " K=14 convolutional code. ! Plot is from: L. Perez, “Turbo Codes”, chapter 8 of Trellis Coding by C. Schlegel. IEEE Press, 1997. Gain of almost 2 dB! Power Efficiency of Existing Standards Error Correction Coding ! Channel coding adds structured redundancy to a transmission. mxChannel Encoder " The input message m is composed of K symbols. " The output code word x is composed of N symbols. " Since N > K there is redundancy in the output. " The code rate is r = K/N. ! Coding can be used to: " Detect errors: ARQ " Correct errors: FEC Traditional Coding Techniques The Turbo-Principle/Iterative Decoding ! Turbo codes get their name because the decoder uses feedback, like a turbo engine. Theory of Iterative Coding Theory of Iterative Coding(2) Theory of Iterative Coding(3) Theory of Iterative Coding (4) Log Likelihood Algebra New Operator Modulo 2 Addition Example: Product Code Iterative Product Decoding RSC vs NSC Recursive/Systematic Convolutional Coding Concatenated Coding -
A [49 16 6 ]-Linear Code As Product of the [7 4 2 ] Code Due to Aunu and the Hamming [7 4 3 ] Code
General Letters in Mathematics, Vol. 4, No.3 , June 2018, pp.114 -119 Available online at http:// www.refaad.com https://doi.org/10.31559/glm2018.4.3.4 A [49 16 6 ]-Linear Code as Product Of The [7 4 2 ] Code Due to Aunu and the Hamming [7 4 3 ] Code CHUN, Pamson Bentse1, IBRAHIM Alhaji Aminu2, and MAGAMI, Mohe'd Sani3 1 Department Of Mathematics, Plateau State University Bokkos, Jos Nigeria [email protected] 2 Department Of Mathematics, Usmanu Danfodiyo University Sokoto, Sokoto Nigeria [email protected] 3 Department Of Mathematics, Usmanu Danfodiyo University Sokoto, Sokoto Nigeria [email protected] Abstract: The enumeration of the construction due to "Audu and Aminu"(AUNU) Permutation patterns, of a [ 7 4 2 ]- linear code which is an extended code of the [ 6 4 1 ] code and is in one-one correspondence with the known [ 7 4 3 ] - Hamming code has been reported by the Authors. The [ 7 4 2 ] linear code, so constructed was combined with the known Hamming [ 7 4 3 ] code using the ( u|u+v)-construction method to obtain a new hybrid and more practical single [14 8 3 ] error- correcting code. In this paper, we provide an improvement by obtaining a much more practical and applicable double error correcting code whose extended version is a triple error correcting code, by combining the same codes as in [1]. Our goal is achieved through using the product code construction approach with the aid of some proven theorems. Keywords: Cayley tables, AUNU Scheme, Hamming codes, Generator matrix,Tensor product 2010 MSC No: 97H60, 94A05 and 94B05 1. -
Coding Theory: Linear Error-Correcting Codes Coding Theory Basic Definitions Error Detection and Correction Finite Fields Anna Dovzhik
Coding Theory: Linear Error- Correcting Codes Anna Dovzhik Outline Coding Theory: Linear Error-Correcting Codes Coding Theory Basic Definitions Error Detection and Correction Finite Fields Anna Dovzhik Linear Codes Hamming Codes Finite Fields Revisited BCH Codes April 23, 2014 Reed-Solomon Codes Conclusion Coding Theory: Linear Error- Correcting 1 Coding Theory Codes Basic Definitions Anna Dovzhik Error Detection and Correction Outline Coding Theory 2 Finite Fields Basic Definitions Error Detection and Correction 3 Finite Fields Linear Codes Linear Codes Hamming Codes Hamming Codes Finite Fields Finite Fields Revisited Revisited BCH Codes BCH Codes Reed-Solomon Codes Reed-Solomon Codes Conclusion 4 Conclusion Definition A q-ary word w = w1w2w3 ::: wn is a vector where wi 2 A. Definition A q-ary block code is a set C over an alphabet A, where each element, or codeword, is a q-ary word of length n. Basic Definitions Coding Theory: Linear Error- Correcting Codes Anna Dovzhik Definition If A = a ; a ;:::; a , then A is a code alphabet of size q. Outline 1 2 q Coding Theory Basic Definitions Error Detection and Correction Finite Fields Linear Codes Hamming Codes Finite Fields Revisited BCH Codes Reed-Solomon Codes Conclusion Definition A q-ary block code is a set C over an alphabet A, where each element, or codeword, is a q-ary word of length n. Basic Definitions Coding Theory: Linear Error- Correcting Codes Anna Dovzhik Definition If A = a ; a ;:::; a , then A is a code alphabet of size q. Outline 1 2 q Coding Theory Basic Definitions Error Detection Definition and Correction Finite Fields A q-ary word w = w1w2w3 ::: wn is a vector where wi 2 A. -
Mceliece Cryptosystem Based on Extended Golay Code
McEliece Cryptosystem Based On Extended Golay Code Amandeep Singh Bhatia∗ and Ajay Kumar Department of Computer Science, Thapar university, India E-mail: ∗[email protected] (Dated: November 16, 2018) With increasing advancements in technology, it is expected that the emergence of a quantum computer will potentially break many of the public-key cryptosystems currently in use. It will negotiate the confidentiality and integrity of communications. In this regard, we have privacy protectors (i.e. Post-Quantum Cryptography), which resists attacks by quantum computers, deals with cryptosystems that run on conventional computers and are secure against attacks by quantum computers. The practice of code-based cryptography is a trade-off between security and efficiency. In this chapter, we have explored The most successful McEliece cryptosystem, based on extended Golay code [24, 12, 8]. We have examined the implications of using an extended Golay code in place of usual Goppa code in McEliece cryptosystem. Further, we have implemented a McEliece cryptosystem based on extended Golay code using MATLAB. The extended Golay code has lots of practical applications. The main advantage of using extended Golay code is that it has codeword of length 24, a minimum Hamming distance of 8 allows us to detect 7-bit errors while correcting for 3 or fewer errors simultaneously and can be transmitted at high data rate. I. INTRODUCTION Over the last three decades, public key cryptosystems (Diffie-Hellman key exchange, the RSA cryptosystem, digital signature algorithm (DSA), and Elliptic curve cryptosystems) has become a crucial component of cyber security. In this regard, security depends on the difficulty of a definite number of theoretic problems (integer factorization or the discrete log problem). -
James Massey Memorial Service
On June 16, 2013, JaImens L. MRassey, peassmed aweaym at hibs hormea in Cnopcenheagen, Denmark. In recognition of Jim’s great service to and love for Notre Dame, the College of Engineering invites you to join us in honoring him. A memorial Mass will be held on Friday, November 1, at 4:00 p.m. in the Holy Cross Chapel of the Stinson-Remick Hall of Engineering. It will be followed by a reception in the Stinson-Remick atrium. The Mass will be celebrated by the Rev. Edward A. Malloy, C.S.C. , President Emeritus of the University of Notre Dame, and concelebrated by the Rev. Theodore M. Hesburgh , President Emeritus of the University of Notre Dame. All are invited to attend this special event in Jim's honor. So that we can properly plan for the reception, please RSVP to Michele Tharp at [email protected] by Friday, October 4, if you plan to attend. The College of Engineering is also launching a graduate fellowship in electrical engineering in Jim’s name. Tax deductible contributions can be made here and designated for the “James L. Massey Graduate Fellowship in Electrical Engineering.” Questions regarding the fund Department of Electrical Engineering can be directed to Nathan Utz, academic advancement director for , - the College of Engineering, [email protected] . We hope you will Department of Electrical Engineering consider making a generous contribution to this worthy cause. Finally, if you know of other individuals at Notre Dame, in the South Bend area, or in the wider community who knew Jim and The Frank M. -
Coded Computing Via Binary Linear Codes: Designs and Performance Limits Mahdi Soleymani∗, Mohammad Vahid Jamali∗, and Hessam Mahdavifar, Member, IEEE
1 Coded Computing via Binary Linear Codes: Designs and Performance Limits Mahdi Soleymani∗, Mohammad Vahid Jamali∗, and Hessam Mahdavifar, Member, IEEE Abstract—We consider the problem of coded distributed processing capabilities. A coded computing scheme aims to computing where a large linear computational job, such as a divide the job to k < n tasks and then to introduce n − k matrix multiplication, is divided into k smaller tasks, encoded redundant tasks using an (n; k) code, in order to alleviate the using an (n; k) linear code, and performed over n distributed nodes. The goal is to reduce the average execution time of effect of slower nodes, also referred to as stragglers. In such a the computational job. We provide a connection between the setup, it is often assumed that each node is assigned one task problem of characterizing the average execution time of a coded and hence, the total number of encoded tasks is n equal to the distributed computing system and the problem of analyzing the number of nodes. error probability of codes of length n used over erasure channels. Recently, there has been extensive research activities to Accordingly, we present closed-form expressions for the execution time using binary random linear codes and the best execution leverage coding schemes in order to boost the performance time any linear-coded distributed computing system can achieve. of distributed computing systems [6]–[18]. However, most It is also shown that there exist good binary linear codes that not of the work in the literature focus on the application of only attain (asymptotically) the best performance that any linear maximum distance separable (MDS) codes. -
Introduction to Coding Theory
Introduction Why Coding Theory ? Introduction Info Info Noise ! Info »?# Sink to Source Heh ! Sink Heh ! Coding Theory Encoder Channel Decoder Samuel J. Lomonaco, Jr. Dept. of Comp. Sci. & Electrical Engineering Noisy Channels University of Maryland Baltimore County Baltimore, MD 21250 • Computer communication line Email: [email protected] WebPage: http://www.csee.umbc.edu/~lomonaco • Computer memory • Space channel • Telephone communication • Teacher/student channel Error Detecting Codes Applied to Memories Redundancy Input Encode Storage Detect Output 1 1 1 1 0 0 0 0 1 1 Error 1 Erasure 1 1 31=16+5 Code 1 0 ? 0 0 0 0 EVN THOUG LTTRS AR MSSNG 1 16 Info Bits 1 1 1 0 5 Red. Bits 0 0 0 0 0 0 0 FRM TH WRDS N THS SNTNCE 1 1 1 1 0 0 0 0 1 1 1 Double 1 IT CN B NDRSTD 0 0 0 0 1 Error 1 Error 1 Erasure 1 1 Detecting 1 0 ? 0 0 0 0 1 1 1 1 Error Control Coding 0 0 1 1 0 0 31% Redundancy 1 1 1 1 Error Correcting Codes Applied to Memories Input Encode Storage Correct Output Space Channel 1 1 1 1 0 0 0 0 Mariner Space Probe – Years B.C. ( ≤ 1964) 1 1 Error 1 1 • 1 31=16+5 Code 1 0 1 0 0 0 0 Eb/N0 Pe 16 Info Bits 1 1 1 1 -3 0 5 Red. Bits 0 0 0 6.8 db 10 0 0 0 0 -5 1 1 1 1 9.8 db 10 0 0 0 0 1 1 1 Single 1 0 0 0 0 Error 1 1 • Mariner Space Probe – Years A.C. -
2010 Roster (V: Indicates Voting Member of Bog)
IEEE Information Theory Society 2010 Roster (v: indicates voting member of BoG) Officers Frank Kschischang President v Giuseppe Caire First Vice President v Muriel M´edard Second Vice President v Aria Nosratinia Secretary v Nihar Jindal Treasurer v Andrea Goldsmith Junior Past President v Dave Forney Senior Past President v Governors Until End of Alexander Barg 2010 v Dan Costello 2010 v Michelle Effros 2010 v Amin Shokrollahi 2010 v Ken Zeger 2010 v Helmut B¨olcskei 2011 v Abbas El Gamal 2011 v Alex Grant 2011 v Gerhard Kramer 2011 v Paul Siegel 2011 v Emina Soljanin 2011 v Sergio Verd´u 2011 v Martin Bossert 2012 v Max Costa 2012 v Rolf Johannesson 2012 v Ping Li 2012 v Hans-Andrea Loeliger 2012 v Prakash Narayan 2012 v Other Voting Members of BoG Ezio Biglieri IT Transactions Editor-in-Chief v Bruce Hajek Chair, Conference Committee v total number of voting members: 27 quorum: 14 1 Standing Committees Awards Giuseppe Caire Chair, ex officio 1st VP Muriel M´edard ex officio 2nd VP Alexander Barg new Max Costa new Elza Erkip new Ping Li new Andi Loeliger new Ueli Maurer continuing En-hui Yang continuing Hirosuke Yamamoto new Ram Zamir continuing Aaron D. Wyner Award Selection Frank Kschischang Chair, ex officio President Giuseppe Caire ex officio 1st VP Andrea Goldsmith ex officio Junior PP Dick Blahut new Jack Wolf new Claude E. Shannon Award Selection Frank Kschischang Chair, ex officio President Giuseppe Caire ex officio 1st VP Muriel M´edard ex officio 2nd VP Imre Csisz`ar continuing Bob Gray continuing Abbas El Gamal new Bob Gallager new Conference