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Short Low-Rate Non-Binary Turbo Codes Gianluigi Liva, Bal´Azs Matuz, Enrico Paolini, Marco Chiani
Short Low-Rate Non-Binary Turbo Codes Gianluigi Liva, Bal´azs Matuz, Enrico Paolini, Marco Chiani Abstract—A serial concatenation of an outer non-binary turbo decoding thresholds lie within 0.5 dB from the Shannon code with different inner binary codes is introduced and an- limit in the coherent case, for a wide range of coding rates 1 alyzed. The turbo code is based on memory- time-variant (1/3 ≤ R ≤ 1/96). Remarkably, a similar result is achieved recursive convolutional codes over high order fields. The resulting codes possess low rates and capacity-approaching performance, in the noncoherent detection framework as well. thus representing an appealing solution for spread spectrum We then focus on the specific case where the inner code is communications. The performance of the scheme is investigated either an order-q Hadamard code or a first order length-q Reed- on the additive white Gaussian noise channel with coherent and Muller (RM) code, due to their simple fast Hadamard trans- noncoherent detection via density evolution analysis. The pro- form (FHT)-based decoding algorithms. The proposed scheme posed codes compare favorably w.r.t. other low rate constructions in terms of complexity/performance trade-off. Low error floors can be thus seen either as (i) a serial concatenation of an outer and performances close to the sphere packing bound are achieved Fq-based turbo code with an inner Hadamard/RM code with down to small block sizes (k = 192 information bits). antipodal signalling, or (ii) as a coded modulation Fq-based turbo/LDPC code with q-ary (bi-) orthogonal modulation. -
Orthogonal Arrays and Codes
Orthogonal Arrays & Codes Orthogonal Arrays - Redux An orthogonal array of strength t, a t-(v,k,λ)-OA, is a λvt x k array of v symbols, such that in any t columns of the array every one of the possible vt t-tuples of symbols occurs in exactly λ rows. We have previously defined an OA of strength 2. If all the rows of the OA are distinct we call it simple. If the symbol set is a finite field GF(q), the rows of an OA can be viewed as vectors of a vector space V over GF(q). If the rows form a subspace of V the OA is said to be linear. [Linear OA's are simple.] Constructions Theorem: If there exists a Hadamard matrix of order 4m, then there exists a 2-(2,4m-1,m)-OA. Pf: Let H be a standardized Hadamard matrix of order 4m. Remove the first row and take the transpose to obtain a 4m by 4m-1 array, which is a 2-(2,4m-1,m)-OA. a a a a a a a a a a b b b b 2-(2,7,2)-OA a b b a a b b a b b b b a a constructed from an b a b a b a b order 8 Hadamard b a b b a b a matrix b b a a b b a b b a b a a b Linear Constructions Theorem: Let M be an mxn matrix over Fq with the property that every t columns of M are linearly independent. -
TC08 / 6. Hadamard Codes 3.12.07 SX
TC08 / 6. Hadamard codes 3.12.07 SX Hadamard matrices. Paley’s construction of Hadamard matrices Hadamard codes. Decoding Hadamard codes Hadamard matrices A Hadamard matrix of order is a matrix of type whose coefficients are1 or 1 and such that . Note that this relation is equivalent to say that the rows of have norm √ and that any two distinct rows are orthogonal. Since is invertible and , we see that 2 and hence is also a Hadamard matrix. Thus is a Hadamard matrix if and only if its columns have norm √ and any two distinct columns are orthogonal. If is a Hadamard matrix of order , then det ⁄ . In particular we see that the Hadamard matrices satisfy the equality in Hadamard’s inequality: / |det| ∏∑ , which is valid for all real matrices of order . Remark. The expression / is the supremum of the value of det when runs over the real matrices such that 1. Moreover, the equality is reached if and only if is a Hadamard matrix. 3 If we change the signs of a row (column) of a Hadamard matrix, the result is clearly a Hadamard matrix. If we permute the rows (columns) of a Hadamard matrix, the result is another Hadamard matrix. Two Hadamard matrices are called equivalent (or isomorphic) if it is to go from one to the other by means of a sequence of such operations. Observe that by changing the sign of all the columns that begin with 1, and afterwards all the rows that begin with 1, we obtain an equivalent Hadamard matrix whose first row and first column only contain 1. -
A Simple Low Rate Turbo-Like Code Design for Spread Spectrum Systems Durai Thirupathi and Keith M
A simple low rate turbo-like code design for spread spectrum systems Durai Thirupathi and Keith M. Chugg Communication Sciences Institute Dept. of Electrical Engineering University of Southern California, Los Angeles 90089-2565 thirupat,chugg ¡ @usc.edu Abstract chine. The disadvantage of the SOTC is that the decoding com- plexity increases dramatically with decrease in code rate. On In this paper, we introduce a simple method to construct the other hand, THC, which is constructed using weaker con- very low rate recursive systematic convolutional codes from a stituent codes has slower rate of convergence which might not standard rate- ¢¤£¦¥ convolutional code. These codes in turn are be a desired property for practical applications. So, in design- used in parallel concatenation to obtain very low rate turbo like ing very low rate turbo-like codes for practical applications, one codes. The resulting codes are rate compatible and require low of the critical issues is to design strong enough constituent con- complexity decoders. Simulation results show that an additional volutional codes with decoding complexity of the overall code coding gain of 0.9 dB in additive white Gaussian noise (AWGN) being almost independent of the code rate. channel and 2 dB in Rayleigh fading channel is possible com- In this paper, we introduce a technique to construct such a pared to rate-1/3 turbo code. The low rate coding scheme in- class of low rate convolutional codes. These codes are then creases the capacity by more than 25% when applied to multi- used to build very low rate turbo codes. Since these codes are ple access environments such as Code Division Multiple Access constructed from rate- ¢¤£¦¥ parent codes, the complexity of the (CDMA). -
Local List-Decoding of Reed-Muller Codes Over F2 Original Paper by Gopalan, Klivans, and Zuckerman [6, 7]
Local List-Decoding of Reed-Muller Codes over F2 Original paper by Gopalan, Klivans, and Zuckerman [6, 7] Sahil Singla Manzil Zaheer Computer Science Department Electrical and Computer Engineering Carnegie Mellon University Carnegie Mellon University [email protected] [email protected] December 7, 2014 Abstract In this report we study the paper titled, \List-Decoding Reed-Muller Codes over Small Fields" by Parikshit Gopalan, Adam R. Klivans and David Zuckerman [6, 7]. The Reed-Muller codes are multivariate generalization of Reed-Solomon codes, which use polynomials in multiple variables to encode messages through functional encoding. Next, any list decoding problem for a code has two facets: Firstly, what is the max- imal radius up to which any ball of that radius contains only a constant number of codewords. Secondly, how to find these codewords in an efficient manner. The paper by GKZ presents the first local list-decoding algorithm for the r-th order Reed-Muller code RM(r; m) over F2 for r ≥ 2. Given an oracle for a received word m R : F2 ! F2, their randomized local list-decoding algorithm produces a list containing all degree r polynomials within relative distance (2−r − ) from R for any > 0 in time poly(mr; r). Since RM(r; m) has relative distance 2r, their algorithm beats the Johnson bound for r ≥ 2. Moreover, as the list size could be exponential in m at radius 2−r, their bound is optimal in the local setting. 1 Contents 1 Introduction 3 1.1 Basics of Code . .3 1.1.1 Johnson Bound . -
TC+0 / 6. Hadamard Codes S
TC+0 / 6. Hadamard codes S. Xambó Hadamard matrices. Paley’s construction of Hadamard matrices Hadamard codes. Decoding Hadamard codes Hadamard matrices A Hadamard matrix of order is a matrix of type whose coefficients are 1 or 1 and such that . Note that this relation is equivalent to say that the rows of have norm √ and that any two distinct rows are orthogonal. Since is invertible and we see that 2 and hence is also a Hadamard matrix. Thus is a Hadamard matrix if and only if its columns have norm √ and any two distinct columns are orthogonal. If is a Hadamard matrix of order , then det ⁄ . In particular we see that the Hadamard matrices satisfy the equality in Hadamard’s inequality: / |det| ∏∑ which is valid for all real matrices of order . Remark. The expression / is the supremum of the value of det when runs over the real matrices such that 1. Moreover, the equality is reached if and only if is a Hadamard matrix. 3 If we change the signs of a row (column) of a Hadamard matrix, the result is clearly a Hadamard matrix. If we permute the rows (columns) of a Hadamard matrix, the result is another Hadamard matrix. Two Hadamard matrices are called equivalent (or isomorphic) if it is possible to go from one to the other by means of a sequence of such operations. Observe that by changing the sign of all the columns that begin with 1 and afterwards of all the rows that begin with 1 we obtain an equivalent Hadamard matrix whose first row and first column only contain 1. -
An Ultimate-Shannon-Limit-Approaching Gbps Throughput Encoder/Decoder System S
1 An Ultimate-Shannon-Limit-Approaching Gbps Throughput Encoder/Decoder System S. Jiang, P. W. Zhang, F. C. M. Lau and C.-W. Sham Abstract—A turbo-Hadamard code (THC) is a type of low-rate component of the encoding/decoding system is fully opti- channel code with capacity approaching the ultimate Shannon mized to achieve high hardware-utilization rate. Arrange- − limit, i.e., 1.59 dB. In this paper, we investigate the hardware ment is made to ensure the data corresponding to different design of a turbo-Hadamard encoder/decoder system. The entire system has been implemented on an FPGA board. A bit error codewords are in an orderly manner such that they can be −5 rate (BER) of 10 can be achieved at Eb/N0 = 0.04 dB with received/stored/retrieved/processed efficiently at the decoder. a throughput of 3.2 Gbps or at Eb/N0 = −0.45 dB with a Last but not the least, we construct rate-adaptive THCs by throughput of 1.92 Gbps. puncturing the parity bits of the code. Sect. II briefly reviews the THC. Sect. III describes our overall design of the THC encoder/decoder system and evaluates the latency of each sub- I. INTRODUCTION decoder. Sect. IV shows the FPGA implementation results, Turbo code, low-density parity-check (LDPC) code, and including hardware utilization, throughput and bit error rate polar code are the most widely studied and implemented performance. Finally, Sect. ?? provides some concluding re- error-correction codes over the last two-and-a-half decades marks. because of their capacity-approaching capabilities [1], [2], [3], [4], [5], [6]. -
Math 550 Coding and Cryptography Workbook J. Swarts 0121709 Ii Contents
Math 550 Coding and Cryptography Workbook J. Swarts 0121709 ii Contents 1 Introduction and Basic Ideas 3 1.1 Introduction . 3 1.2 Terminology . 4 1.3 Basic Assumptions About the Channel . 5 2 Detecting and Correcting Errors 7 3 Linear Codes 13 3.1 Introduction . 13 3.2 The Generator and Parity Check Matrices . 16 3.3 Cosets . 20 3.3.1 Maximum Likelihood Decoding (MLD) of Linear Codes . 21 4 Bounds for Codes 25 5 Hamming Codes 31 5.1 Introduction . 31 5.2 Extended Codes . 33 6 Golay Codes 37 6.1 The Extended Golay Code : C24. ....................... 37 6.2 The Golay Code : C23.............................. 40 7 Reed-Muller Codes 43 7.1 The Reed-Muller Codes RM(1, m) ...................... 46 8 Decimal Codes 49 8.1 The ISBN Code . 49 8.2 A Single Error Correcting Decimal Code . 51 8.3 A Double Error Correcting Decimal Code . 53 iii iv CONTENTS 8.4 The Universal Product Code (UPC) . 56 8.5 US Money Order . 57 8.6 US Postal Code . 58 9 Hadamard Codes 61 9.1 Background . 61 9.2 Definition of the Codes . 66 9.3 How good are the Hadamard Codes ? . 67 10 Introduction to Cryptography 71 10.1 Basic Definitions . 71 10.2 Affine Cipher . 73 10.2.1 Cryptanalysis of the Affine Cipher . 74 10.3 Some Other Ciphers . 76 10.3.1 The Vigen`ereCipher . 76 10.3.2 Cryptanalysis of the Vigen`ereCipher : The Kasiski Examination . 77 10.3.3 The Vernam Cipher . 79 11 Public Key Cryptography 81 11.1 The Rivest-Shamir-Adleman (RSA) Cryptosystem . -
Background on Coding Theory
6.895 PCP and Hardness of Approximation MIT, Fall 2010 Lecture 3: Coding Theory Lecturer: Dana Moshkovitz Scribe: Michael Forbes and Dana Moshkovitz 1 Motivation In the course we will make heavy use of coding theory. In this lecture we review the basic ideas and constructions. We start with two motivating examples. 1.1 Noisy Communication Alice gets a k-bit message x to send to Bob. Unfortunately, the communication channel is corrupted, and some number of bits may flip. For conceretness, say twenty percent of all bits sent on the channel may flip. Which bits are flipped is unknown, and different bits may flip for different messages sent on the channel. Can Alice still send a message that can be reliably received by Bob? We allow Alice and Bob to make any agreements prior to Alice learning about her message x. We also allow Alice to send more than k bits on the channel. The redundant bits can compesate for the bits lost due to corruption. We will see that Alice can send only n = Θ(k) bits of information about her message, such that even if twenty percent of those bits are flipped, the mistakes can be detected, and all of the original k bits can be recovered by Bob! 1.2 Equality Testing The following example is a classic example from communication complexity. Its setup and ideas are very useful for understanding PCPs. Suppose there are two players, Alice and Bob, as well as a verifier. Each player receives a private k-bit string. Alice's string is denoted x, and Bob's string is denoted y. -
An Introduction of the Theory of Nonlinear Error-Correcting Codes
Rochester Institute of Technology RIT Scholar Works Theses 1987 An introduction of the theory of nonlinear error-correcting codes Robert B. Nenno Follow this and additional works at: https://scholarworks.rit.edu/theses Recommended Citation Nenno, Robert B., "An introduction of the theory of nonlinear error-correcting codes" (1987). Thesis. Rochester Institute of Technology. Accessed from This Thesis is brought to you for free and open access by RIT Scholar Works. It has been accepted for inclusion in Theses by an authorized administrator of RIT Scholar Works. For more information, please contact [email protected]. An Introduction to the Theory of Nonlinear Error-Correcting Codes Robert B. Nenno Rochester Institute of Technology ABSTRACT Nonlinear error-correcting codes are the topic of this thesis. As a class of codes, it has been investigated far less than the class of linear error-correcting codes. While the latter have many practical advantages, it the former that contain the optimal error-correcting codes. In this project the theory (with illustrative examples) of currently known nonlinear codes is presented. Many definitions and theorems (often with their proofs) are presented thus providing the reader with the opportunity to experience the necessary level of mathematical rigor for good understanding of the subject. Also, the examples will give the reader the additional benefit of seeing how the theory can be put to use. An introduction to a technique for finding new codes via computer search is presented. Categories and Subject Descriptors: E.4 [Coding and Information Theory] For mal models of communication; H.l.l [Models and Principles] Systems and Infor mation Theory General Terms: Algorithms, Theory Additional Key Words and Phrases: Bounds on codes, designs, nongroup codes, Hadamard matrices, nonlinear error-correcting codes, uniformly packed codes October 8, 1987 TABLE OF CONTENTS Chapter 1 . -
Coding Vs. Spreading for Narrow-Band Interference Suppression
1 Coding vs. Spreading for Narrow-Band Interference Suppression Xiaofu Wu and Zhen Yang Abstract—The use of active narrow-band interference (NBI) suppression in spread-spectrum systems. In general, there are suppression in direct-sequence spread-spectrum (DS-SS) com- two categories for these techniques, one is based on linear munications has been extensively studied. In this paper, we signal processing techniques [3] and the other employs model- address the problem of optimum coding-spreading tradeoff for NBI suppression. With maximum likelihood decoding, we based techniques [1], including nonlinear filtering techniques first derive upper bounds on the error probability of coded and multiuser detection techniques. In [2], [4], a code-aided systems in the presence of a special class of NBI, namely, approach was proposed by Poor and Wang for NBI suppression multi-tone interference with orthogonal signatures. By employ- in direct-sequence code-division multiple-access (DS/CDMA) ing the well-developed bounding techniques, we show there is networks. This method, which is based on the minimum mean no advantage in spreading, and hence a low-rate full coding approach is always preferred. Then, we propose a practical square error (MMSE) linear detector, has been shown to out- low-rate turbo-Hadamard coding approach, in which the NBI perform all of the previous linear or nonlinear methods for NBI suppression is naturally achieved through iterative decoding. The suppression. In recent years, NBI suppression has also been proposed turbo-Hadamard coding approach employs a kind of considered in ultra-wide bandwidth (UWB) communications coded spread-spectrum signalling with time-varying spreading [5]–[9]. -
Walsh Codes, PN Sequences and Their Role in CDMA Technology Term Paper - EEL 201 Kunal Singhal, 2012CS10231 Student, CSE Department, IIT Delhi
1 Walsh Codes, PN Sequences and their role in CDMA Technology Term Paper - EEL 201 Kunal Singhal, 2012CS10231 Student, CSE Department, IIT Delhi 1 1 Abstract—Walsh codes are error correcting orthogonal codes H1 = 1 H2 = and PN sequences are deterministically generated sequences 1 −1 which appear to be random noises. Both of these concepts HN HN are used in error free communication. This paper outlines H2N = HN −HN properties of Walsh codes and PN sequences and discuss the For correctness, we see that, practical implementation in software and hardware. The paper T T T HN HN HN HN explores and model Walsh Codes and Hadamard matrices as a H2N H2N = T T finite orthogonal vector space. It further describe their role in HN −HN HN −HN T T T T communication technologies in particular CDMA. HN HN + HN HN HN HN − HN HN = T T T T Index Terms—Walsh code, Pseudo-Noise sequences, PN se- HN HN − HN HN HN HN + HN HN quence, generator matrix, recursion, hamming weight, hamming 2IN 0 distance, locally decodable, Hadamard matrices, linear codes, = = 2I2N 0 2IN pseudorandom sequences, shift registers, spreading spectrum technique, CDMA, Cryptographic Secure PN codes Walsh codes can be generated from Hadamard matrices of orders which are a power of 2. The rows of the matrix of order 2N constitutes the Walsh codes which encodes N I. INTRODUCTION bit sequences. Now, instead of 1 and -1 consider 1 and 0. ALSH codes are mutually orthogonal error correcting That is consider the matrix and the codes over the field F2 or W codes.