New Developments in Q-Polynomial Codes

Total Page:16

File Type:pdf, Size:1020Kb

New Developments in Q-Polynomial Codes New developments in q-polynomial codes Chuan Lv, Tongjiang Yan & Guozhen Xiao Cryptography and Communications Discrete Structures, Boolean Functions and Sequences ISSN 1936-2447 Cryptogr. Commun. DOI 10.1007/s12095-015-0147-4 1 23 Your article is protected by copyright and all rights are held exclusively by Springer Science +Business Media New York. This e-offprint is for personal use only and shall not be self- archived in electronic repositories. If you wish to self-archive your article, please use the accepted manuscript version for posting on your own website. You may further deposit the accepted manuscript version in any repository, provided it is only made publicly available 12 months after official publication or later and provided acknowledgement is given to the original source of publication and a link is inserted to the published article on Springer's website. The link must be accompanied by the following text: "The final publication is available at link.springer.com”. 1 23 Author's personal copy Cryptogr. Commun. DOI 10.1007/s12095-015-0147-4 New developments in q-polynomial codes Chuan Lv1 · Tongjiang Yan2 · Guozhen Xiao1 Received: 19 March 2015 / Accepted: 12 June 2015 © Springer Science+Business Media New York 2015 Abstract Cyclic codes are prominently used in electronics and communication engineer- ing. A new view on cyclic codes based on q-polynomials has been introduced by Ding and Ling. This paper is concerned with new developments in cyclic codes from q-polynomials. The properties of the q-polynomial codes and the fundamental relations between q- polynomial codes and generator polynomials are proposed. Then a new design of t-error correcting codes is introduced. Several constructions of new q-polynomial codes from old ones are also presented. Keywords Cyclic codes · Linearized polynomial · q-Polynomial · Trace function Mathematics Subject Classification (2010) 94B15 · 94B05 · 05B50 1 Introduction Let q beapowerofaprime,alinear[n, k, d; q] code is a k-dimensional subspace of GF(q) with minimum nonzero (Hamming) weight d. A linear [n, k] code C over GF(q) is called cyclic if (c0,c1, ··· ,cn−1) ∈ C implies (cn−1,c1,c2, ··· ,cn−2) ∈ C. By identifying any The work is supported by the National Natural Science Foundations of China (No.61170319), the Shandong Provincial Natural Science Foundation of China(No. ZR2014FQ005) and the Fundamental Research Funds for the Central Universities of China(No. 15CX02081A). Chuan Lv [email protected] Tongjiang Yan [email protected] 1 State Key Laboratory of ISN, Xidian University, Xi’an 710071, People’s Republic of China 2 School of Sciences, China University of Petroleum, Qingdao 366580, People’s Republic of China Author's personal copy Cryptogr. Commun. n vector (c0,c1, ··· ,cn−1) ∈ GF(q) with a polynomial 2 n−1 n c0 + c1x + c2x +···+cn−1x ∈ GF(q)[x]/(x − 1), any code C of length n over GF(q) corresponds to a subset of the quotient ring GF(q)[x]/(xn − 1). A linear code C is cyclic if and only if the corresponding subset is an ideal of the ring GF(q)[x]/(xn − 1). Noting that every ideal of GF(q)[x]/(xn − 1) is prin- cipal, any cyclic code C can be expressed as C = (g(x)),whereg(x) is monic and has the smallest degree among all the generators of C.Theng(x) is unique and called the generator polynomial, and h(x) = (xn − 1)/g(x) is referred to as the parity-check polynomial of C. Cyclic codes have applications in storage and communication systems because they have efficient encoding and decoding algorithms [2, 3, 5]. Cyclic codes have been studied for decades and a lot of progress has been made. Three approaches are generally used in the design and analysis of cyclic codes, while they are based on generator matrices, generator polynomials and idempotents respectively. Ding and Ling introduced a new approach to those of cyclic codes based on q-polynomials and constructed some new cyclic codes[4]. The main concerns of this paper are to build the fundamental theory of the q-polynomial codes and to give some constructions of the cyclic codes from the q-polynomial approach. The remainder parts of this paper are organized as follows. Section 2 gives some nota- tions for this paper, some properties of q-polynomials and several lemmas. The relation between generator polynomials and q-polynomial codes is discussed in Section 3. In Sec- tion 4,anewdesignoft-error correcting codes which are called q-BCH codes is introduced and the dimensions of such codes are considered. Several constructions of cyclic codes from original q-polynomial codes are presented in Section 5. Section 6 summarizes this paper. 2 Preliminaries Throughout this paper, we adopt the following notations: • p is a prime. • q is a positive power of p. • n is a positive integer and is used to denote the length of a cyclic code over GF(q). • r = qn. • t s | Trqt /qs (x) is the trace function from GF(q ) to GF(q ),wheres t. • A B is the direct sum of the two subspaces A and B. • DimA is the dimension of the space A. A q-polynomial, or a linearized polynomial over GF(q) is a polynomial of the form = h qi L(x) i=0 lix with all coefficients li in GF(q) and h being a nonnegative integer. The = h i = h qi polynomials l(x) i=0 lix and L(x) i=0 lix over GF(q) are called q-associates of each other. More specially, l(x) is the conventional q-associate of L(x) and L(x) is the linearized q-associate of l(x).Giventwoq-polynomials L1(x) and L2(x), the symbolic multiplication of them is defined by L(x) = L1(x) L2(x) = L1(L2(x)) = L2(L1(x)). Both L1(x) and L2(x) symbolically divide L(x). In the following we give an definition and some lemmas which are needed in this paper. Definition 1 [8]LetL(x) be a nonzero q-polynomial over GF(q). A root ζ of L(x) is called a q-primitive root over GF(q) if it is not a root of any nonzero q-polynomial over GF(q) of lower degree. Author's personal copy Cryptogr. Commun. Lemma 1 [8] Let L1(x) and L2(x) be q-polynomials over GF(q) with conventional = = q-associates l1(x) and l2(x), respectively. Then l(x) l1(x)l2(x) and L(x) L1(x) L2(x) are q-associates of each other. Lemma 2 [8] Let L1(x) and L(x) be q-polynomials over GF(q) with conventional q- associates l1(x) and l(x), respectively. Then the following properties are equivalent: (i) L1(x) symbolically divides L(x); (ii) L1(x) divides L(x); (iii) l1(x) divides l(x). Lemma 3 [9] Let C be a cyclic code with generator polynomial g(x) and parity-check polynomial h(x) = (xn − 1)/g(x). The dual code C⊥ is cyclic and has the generator polynomial ⊥ − g (x) = xdegh(x)h(x 1). n n Lemma 4 [8] Let x −1 = f1(x)f2(x) ···fm(x) be the decomposition of x −1 into monic irreducible factors over GF(q).If(n, q) = 1, there are no multiple factors. Cyclic code is called maximal cyclic code if it is generated by an irreducible factor n fi(x), and is called irreducible cyclic code if it is generated by x − 1/f i(x)[8]. Any cyclic code can be represented as a direct sum of irreducible cyclic codes, which implies that the number of the cyclic codes depends on the factorization of xn − 1inGF(q).If(q, n) = 1, the number is equal to 2m by Lemma 4. 3 Generator polynomials and q-polynomial codes Let q be a prime power, n be a positive integer and r = qn and λ be an element of GF(r)∗. A q-polynomial code with the check element λ is defined in [4]by n−1 n qi Cλ = (c0,c1, ··· ,cn−1) ∈ GF(q) : C(λ) = 0, where C(x) = cix . (1) i=0 Ding and Ling studied the properties of Cλ and proved the following: Proposition 1 [4] Every cyclic code of length n over GF(q) can be expressed as the code n Cλ forsomeelementλ ∈ GF(q ), and is thus a q-polynomial code. A constructive method basing on initial seed sequences is employed to find λ of Cλ for a given cyclic code in [4]. Hereafter we give the relation between the generator polynomial of the cyclic code and the check element λ of the corresponding q-polynomial code Cλ,then give another proof of Proposition 1. By the Normal Basis Theorem [7], GF(r) has a normal n−1 basis {α, αq , ··· ,αq } over GF(q),whereα ∈ GF(r)∗ and α is called a normal element of GF(r) over GF(q).Thenλ has a unique expression of the form n−1 qi λ = λiα , (2) i=0 where each λi ∈ GF(q). Since the normal element α is a q-primitive root of q-polynomial n xq −x, there exists no q-polynomial L(x) with the degree less than qn such that L(α) = 0. Author's personal copy Cryptogr. Commun. = n−1 qi = Let (x) i=0 λix ,thenλ (α).Theq-polynomial code can be denoted by n−1 n qi Cλ = (c0,c1, ··· ,cn−1) ∈ GF(q) : C((α)) = C(α) (α) = 0, where C(x) = ci x . (3) i=0 In the following we give Theorems 1 and 2 to illustrate the one-to-one correspondence between q-polynomial codes and cyclic codes.
Recommended publications
  • Reed-Solomon Encoding and Decoding
    Bachelor's Thesis Degree Programme in Information Technology 2011 León van de Pavert REED-SOLOMON ENCODING AND DECODING A Visual Representation i Bachelor's Thesis | Abstract Turku University of Applied Sciences Degree Programme in Information Technology Spring 2011 | 37 pages Instructor: Hazem Al-Bermanei León van de Pavert REED-SOLOMON ENCODING AND DECODING The capacity of a binary channel is increased by adding extra bits to this data. This improves the quality of digital data. The process of adding redundant bits is known as channel encod- ing. In many situations, errors are not distributed at random but occur in bursts. For example, scratches, dust or fingerprints on a compact disc (CD) introduce errors on neighbouring data bits. Cross-interleaved Reed-Solomon codes (CIRC) are particularly well-suited for detection and correction of burst errors and erasures. Interleaving redistributes the data over many blocks of code. The double encoding has the first code declaring erasures. The second code corrects them. The purpose of this thesis is to present Reed-Solomon error correction codes in relation to burst errors. In particular, this thesis visualises the mechanism of cross-interleaving and its ability to allow for detection and correction of burst errors. KEYWORDS: Coding theory, Reed-Solomon code, burst errors, cross-interleaving, compact disc ii ACKNOWLEDGEMENTS It is a pleasure to thank those who supported me making this thesis possible. I am thankful to my supervisor, Hazem Al-Bermanei, whose intricate know- ledge of coding theory inspired me, and whose lectures, encouragement, and support enabled me to develop an understanding of this subject.
    [Show full text]
  • Error-Correcting Codes
    Error-Correcting Codes Matej Boguszak Contents 1 Introduction 2 1.1 Why Coding? . 2 1.2 Error Detection and Correction . 3 1.3 Efficiency Considerations . 8 2 Linear Codes 11 2.1 Basic Concepts . 11 2.2 Encoding . 13 2.3 Decoding . 15 2.4 Hamming Codes . 20 3 Cyclic Codes 23 3.1 Polynomial Code Representation . 23 3.2 Encoding . 25 3.3 Decoding . 27 3.4 The Binary Golay Code . 30 3.5 Burst Errors and Fire Codes . 31 4 Code Performance 36 4.1 Implementation Issues . 36 4.2 Test Description and Results . 38 4.3 Conclusions . 43 A Glossary 46 B References 49 1 2 1 Introduction Error-correcting codes have been around for over 50 years now, yet many people might be surprised just how widespread their use is today. Most of the present data storage and transmission technologies would not be conceiv- able without them. But what exactly are error-correcting codes? This first chapter answers that question and explains why they are so useful. We also explain how they do what they are designed to do: correct errors. The last section explores the relationships between different types of codes as well the issue of why some codes are generally better than others. Many mathemat- ical details have been omitted in this chapter in order to focus on concepts; a more rigorous treatment of codes follows shortly in chapter 2. 1.1 Why Coding? Imagine Alice wants to send her friend Bob a message. Cryptography was developed to ensure that her message remains private and secure, even when it is sent over a non-secure communication channel, such as the internet.
    [Show full text]
  • Mathematical Introduction to Coding Theory and Cryptography Yi Ouyang
    Mathematical Introduction to Coding Theory and Cryptography Yi Ouyang School of Mathematical Sciences, University of Science and Technology of China Email address: [email protected] Contents Chapter 1. Preliminaries 1 1. Theory of Integers 1 2. Polynomials over a field 4 3. Finite fields 6 Notations 9 Part 1. Coding Theory 11 Chapter 2. Introduction to Coding Theory 13 1. Background 13 2. Basic Definitions 15 Chapter 3. Linear Codes 19 1. Basic definitions 19 2. Hamming codes 23 3. Equivalence of codes 23 4. Encoding and decoding Algorithms 24 Chapter 4. Bounds of codes and codes with good bounds 29 1. Bounds of codes 29 2. Golay Codes 33 3. Other examples of optimal codes 36 Chapter 5. Constructing Codes from Other Codes 39 1. General Rules for Construction 39 2. Reed Muller Codes 41 Chapter 6. Weight Enumerators and the MacWilliams Theorem 47 1. MacWilliams Identity 47 Chapter 7. Sequences over finite fields 53 1. Sequences and Power Series over Finite Fields 53 2. Linear Feedback Shift Registers(LFSR) 57 3. Berlekamp-Massey Algorithm 60 Chapter 8. Cyclic codes and BCH codes 63 1. Cyclic codes 63 2. Trace Expression of Cyclic codes 67 iii iv CONTENTS 3. The BCH codes 69 4. Goppa Code 75 Chapter 9. Generalized GRS codes 79 1. Generalized GRS codes 79 2. Decoding GRS codes 80 Part 2. Cryptography 83 Chapter 10. History and Basic knowledge about Cryptography 85 1. Cryptography from early age 85 Chapter 11. Hard Computational Problems 91 1. Trapdoor function and One-way function 91 2. Factoring and RSA 92 Chapter 12.
    [Show full text]
  • Reed-Solomon Code Encoder/Decoder
    CALIFORNIA STATE UNIVERSITY, NORTHRIDGE (204, 188) REED-SOLOMON CODE ENCODER/DECODER DESIGN, SYNTHESIS, AND SIMULATION WITH QUARTUS ⅱ A graduate project submitted in partial fulfillment of the requirements For the degree of Master of Science in Electrical Engineering By Haoyi Zhang December 2013 The Graduate Project of Haoyi Zhang is approved by: California State University, Northridge ii Table of Contents SIGNATURE PAGE .......................................................................................................... II ABSTRACT ....................................................................................................................... V CHAPTER 1 INTRODUCTION ........................................................................................ 1 1.1 HISTORY OF ERROR CONTROL CODING ............................................................. 1 1.2 THE DEVELOPMENT OF REED-SOLOMON CODES ................................................ 2 1.3 OBJECTIVE ......................................................................................................... 2 1.4 OUTLINE ............................................................................................................ 2 CHAPTER 2 THEORIES OF ERROR CONTROL CODING .......................................... 4 2.1 BASICS OF CODING THEORY .............................................................................. 4 2.1.1 Introduction to the Development of Information Theory and Coding ...... 4 2.1.2 Digital Communication System ...............................................................
    [Show full text]
  • Elements of Coding Theory Error-Detecting and -Correcting Codes
    Elements of Coding Theory Error-detecting and -correcting codes Radu Tr^ımbit¸a¸s UBB January 2013 Radu Tr^ımbit¸a¸s (UBB) Elements of Coding Theory January 2013 1 / 42 OutlineI 1 Hamming's Theory Definitions Hamming Bound 2 Linear Codes Basics Singleton bounds Reed-Solomon Codes Multivariate Polynomial Codes BCH Codes Radu Tr^ımbit¸a¸s (UBB) Elements of Coding Theory January 2013 2 / 42 Hamming's Problem Hamming studied magnetic storage devices. He wanted to build (out of magnetic tapes) a reliable storage medium where data was stored in blocks of size 63 (this is a nice number, we will see why later). When you try to read information from this device, bits may be corrupted, i.e. flipped (from 0 to 1, or 1 to 0). Let us consider the case that at most 1 bit in every block of 63 bits may be corrupted. How can we store the information so that all is not lost? We must design an encoding of the message to a codeword with enough redundancy so that we can recover the original sequence from the received word by decoding. (In Hamming's problem about storage we still say "`received word"') Naive solution { repetition code { to store each bit three times, so that any one bit that is erroneously ipped can be detected and corrected by majority decoding on its block of three. Radu Tr^ımbit¸a¸s (UBB) Elements of Coding Theory January 2013 3 / 42 Basic NotionsI The Hamming encoding tries to do better with the following matrix: 0 1 0 0 0 0 1 1 1 B 0 1 0 0 1 0 1 C G = B C @ 0 0 1 0 1 1 0 A 0 0 0 1 1 1 1 Given a sequence of bits, we chop it into 4 bit chunks.
    [Show full text]
  • Locator Decoding for BCH Codes
    WORDT U hG EL E E ND Locator decoding for BCH codes Juan Silverio Dominguez Y Sainza Supervisor:J. Top Wiskunde Afstudeerverslag Locator decoding for BCHcodes Juan Silverio Dominguez Y Sainza Supervisor:J. Top ' flUi P Crrior :r-tfta I Rekencentn. n , A! Rijksuniversiteit Groningen In form atica Postbus 800 9700 AV Groningen juli 2001 Locator decoding for BCH codes JUAN SILvERI0 DOMINGUEZ Y SAINZA SUPERVISOR: DR. JAAP TOP Contents 1 Introduction 2 1.1 Introduction . 2 1.2The binary [7, 4]-Hamming Code 3 1.3 Notations and definitions 4 2Syndromes and Cyclic Codes 6 2.1 Syndromes 6 2.2Dual code 7 2.3Example: The (7,4)-Hamming Code 8 2.4Cyclic codes 10 2.4.1 BCH and Reed-Solomon codes 12 2.4.2 Fourier transform .14 3Majority Decoding 16 3.1Reed-Muller Codes 16 3.1.1 Reed algorithm 19 4Locator decoding 22 4.1 Locator polynomials and the Peterson algorithm. 22 4.1.1 Example of the Peterson algorithm. 25 4.1.2Linear complexity 27 4.2The algorithms 29 4.2.1 Sugiyama algorithm 31 4.2.2The Sugiyama algorithm in Maple.. 34 4.2.3 Berlekamp-Massey algorithm 35 4.2.4The Berlekamp-Massey algorithm in Maple 39 4.3Forney 40 S Example 42 5.1Example using the Sugiyama algorithm 42 5.2Conclusion 45 Chapter 1 Introduction 1.1Introduction Nowadays digital communication is present in every aspect of our lives: satel- lite data transmissions, network transmissions, computer file transfers, radio com- munications, cellular communications, etc. These transmissions transfer data in- formation through a channel that is prone to error.
    [Show full text]