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We propose a successive cancellation list (SCL) encoding and decoding scheme for the Gelfand Pinsker (GP) problem based on the known nested polar coding scheme. It applies SCL encoding for the source coding part, and SCL decoding with a properly defined CRC for the channel coding part. The scheme shows improved performance compared to the existing method. A known issue with nested polar codes for binary dirty paper is the existence of frozen channel code bits that are not frozen in the source code. These bits need to be retransmitted in a second phase of the scheme, thus reducing the rate and increasing the required blocklength. We provide an improved bound on the size of this set, and on its scaling with respect to the blocklength, when the Bhattacharyya parameter of the test channel used for source coding is sufficiently large, or the Bhattacharyya parameter of the channel seen at the decoder is sufficiently small. The result is formulated for an arbitrary binary-input memoryless GP problem, since unlike the previous results, it does not require degradedness of the two channels mentioned above. Finally, we present simulation results for binary dirty paper and noisy write once memory codes. [ABSTRACT FROM AUTHOR]

In this paper, we formulate the problem to cope with the transmission of extra bits over an existing coded transmission link (referred to as coded payload link) without any cost of extra transmission energy or extra bandwidth. This is possible since a gap to the channel capacity typically exists for a practical code. A new concept, termed as accessible capacity, is introduced to specify the maximum rate at which the superposition transmission of extra bits is reliable and has a negligible effect on the performance of the coded payload link. For a binary-input output-symmetric (BIOS) memoryless channel, the accessible capacity can be characterized as the difference between the channel capacity and the mutual information rate of the coded payload link, which can be numerically evaluated for very short payload codes. For a general payload code, we present a simple lower bound on the accessible capacity, given by the channel capacity minus the coding rate of the payload code. We then focus on the scenarios where low-density parity-check (LDPC) codes are implemented for the payload link. We propose to transmit extra bits by random superposition for encoding, and exhaustive search (with the aid of statistical learning) for decoding. We further propose, by establishing an auxiliary channel (called syndrome channel) induced from “zero-forcing” over the binary field, to transmit extra bits with structured codes such as repetition codes and first-order Reed-Muller (RM) codes. Numerical results show that up to 60 extra bits can be reliably transmitted along with a rate-1/2 LDPC code of length 8064. [ABSTRACT FROM AUTHOR]

Deletion errors are notoriously difficult to correct. The capacity of the binary deletion channel is not yet fully known, and there is no completely satisfactory solution even to the specific problem of correcting only two deletion errors. In this paper, we show that polarization theory, along with the powerful methods of polar coding and successive-cancellation decoding, can be extended to channels with deletion errors. Our results further generalize to channels corrupted by insertion errors and/or combinations of insertions and deletions. It was recently proposed to correct deletion errors using polar codes designed for the BEC, precoded with a sufficiently powerful CRC code. In this approach, in order to correct ${d}$ deletions in a codeword of length ${n}$ , successive-cancellation decoding is run separately for each of the $\binom {n}{d}$ possible deletion patterns, while treating the deleted symbols as erasures. The resulting complexity of decoding is ${O}\bigl ({n}^{d+1}\log {n}\bigr)$. In contrast, we develop herein a natural generalization of successive-cancellation decoding to channels with deletion errors. Our algorithm is based on the recursive structure of polar codes, processing the channel output in ${m} = \log _{2} {n}$ decoding layers, just like the conventional successive-cancellation decoder. Every node in each decoding layer propagates its uncertainty about the deletion pattern to the nodes in the next layer and, eventually, the correct deletion pattern becomes visible at the decoder output, with high probability. This makes it possible to consider at most $\binom {d+2}{2}$ scenarios at each node, and the overall decoding complexity is only ${O}\bigl ({d}^{3} {n} \log {n}\bigr)$ , which scales polynomially rather than exponentially with the number of deletions. Based on the proposed algorithm, we also investigate the channel polarization phenomenon. We are able to prove weak polarization where the number of deletions ${d}$ is small, i.e. ${d}={o}({n})$. We also conjecture the strong polarization for when ${d}={O}(1)$ and provide some evidence to support this conjecture. The strong polarization, if proven, implies that our coding scheme achieves the capacity of any binary-input symmetric channel which furthermore introduces a constant number of deletions. [ABSTRACT FROM AUTHOR]

Lattice codes are elegant and powerful structures that not only achieve the capacity of the additive white Gaussian noise (AWGN) channel but are also a key ingredient to many multiterminal schemes that exploit linearity properties. However, constructing lattice codes that can realize these benefits with low complexity is still a challenging problem. In this paper, efficient encoding and decoding algorithms are proposed for multilevel binary low-density parity-check (LDPC) lattices constructed via Construction $\text{D}'$ whose complexity is linear in the total number of coded bits. Moreover, a generalization of Construction $\text{D}'$ is proposed, which relaxes some of the nesting constraints on the parity-check matrices of the component codes, leading to a simpler and improved design. Based on this construction, low-complexity multilevel LDPC lattices are designed whose performance under multistage decoding is comparable to that of polar lattices and close to that of low-density lattice codes on the power-unconstrained AWGN channel. [ABSTRACT FROM AUTHOR]

Symbol-pair codes were introduced by Cassuto and Blaum in 2010 to protect pair errors in symbol-pair read channels. Recently Yaakobi, Bruck and Siegel (2016) generalized this notion to b-symbol codes in order to consider consecutive b errors for a prescribed integer b ≥ 2, and they gave constructions and decoding algorithms. Cyclic codes were considered by various authors as candidates for symbol-pair codes and they established minimum distance bounds on (certain) cyclic codes. In this paper we use algebraic curves over finite fields in order to obtain tight lower and upper bounds on b-symbol Hamming weights of arbitrary cyclic codes over Fq. Here b ≥ 2 is an arbitrary prescribed positive integer and Fq is an arbitrary finite field. We also present a stability theorem for an arbitrary cyclic code C of dimension k and length n: the b-symbol Hamming weight enumerator of C is the same as the k-symbol Hamming weight enumerator of C if k ≤ b ≤ n−1. Moreover, we give improved tight lower and upper bounds on b-symbol Hamming weights of some cyclic codes related to irreducible cyclic codes. Throughout the paper the length n is coprime to q. [ABSTRACT FROM AUTHOR]

We consider the problem of constructing binary codes for correcting deletions that are localized within certain parts of the codeword that are unknown a priori. The model that we study is when $\delta \leq w$ deletions are localized in a window of size $w$ bits. These $\delta $ deletions do not necessarily occur in consecutive positions, but are restricted to the window of size $w$. The localized deletions model is a generalization of the bursty model, in which all the deleted bits are consecutive. In this paper, we construct new explicit codes for the localized model, based on the family of Guess & Check codes which was previously introduced by the authors. The codes that we construct can correct, with high probability, $\delta \leq w$ deletions that are localized in a single window of size $w$ , where $w$ grows with the block length. Moreover, these codes are systematic; have low redundancy; and have efficient deterministic encoding and decoding algorithms. We also generalize these codes to deletions that are localized within multiple windows in the codeword. [ABSTRACT FROM AUTHOR]

In this paper, a general binary-input binary-output channel is investigated in the presence of feedback and input constraints. The feedback capacity and the optimal input distribution of this setting are calculated for the case of an $(1,\infty )$ -RLL input constraint, that is, the input sequence contains no consecutive ones. These results are obtained via explicit solution of an equivalent dynamic programming optimization problem. A simple coding scheme is designed based on the principle of posterior matching, which was introduced by Shayevitz and Feder for memoryless channels. The posterior matching scheme for our input-constrained setting is shown to achieve capacity using two new ideas: history bits, which captures the memory embedded in our setting, and message-interval splitting, which eases the analysis of the scheme. Additionally, in the special case of an S-channel, we give a very simple zero-error coding scheme that is shown to achieve capacity. For the input-constrained binary symmetric channel, we show using our capacity formula that feedback increases capacity when the cross-over probability is small. [ABSTRACT FROM AUTHOR]

This paper studies the parameters for which binary Reed–Muller (RM) codes can be decoded successfully on the binary erasure channel and binary symmetry channel, and, in particular, when can they achieve capacity for these two classical channels. Necessarily, this paper also studies the properties of evaluations of multivariate $GF(2)$ polynomials on the random sets of inputs. For erasures, we prove that RM codes achieve capacity both for very high rate and very low rate regimes. For errors, we prove that RM codes achieve capacity for very low rate regimes, and for very high rates, we show that they can uniquely decode at about the square root of the number of errors at capacity. The proofs of these four results are based on different techniques, which we find interesting in their own right. In particular, we study the following questions about $E(m,r)$ , the matrix whose rows are the truth tables of all the monomials of degree $\leq r$ in $m$ variables. What is the most (resp. least) number of random columns in $E(m,r)$ that define a submatrix having full column rank (resp. full row rank) with high probability? We obtain tight bounds for very small (resp. very large) degrees $r$ , which we use to show that RM codes achieve capacity for erasures in these regimes. Our decoding from random errors follows from the following novel reduction. For every linear code $C$ of sufficiently high rate, we construct a new code $C'$ obtained by tensorizing $C$ , such that for every subset $S$ of coordinates, if $C$ can recover from erasures in $S$ , then $C'$ can recover from errors in $S$ . Specializing this to the RM codes and using our results for erasures imply our result on the unique decoding of the RM codes at high rate. Finally, two of our capacity achieving results require tight bounds on the weight distribution of RM codes. We obtain such bounds extending the recent bounds from constant degree to linear degree polynomials. [ABSTRACT FROM PUBLISHER]

In this paper, code decompositions (a.k.a. code nestings) are used to design binary polarization kernels. The proposed kernels are in general nonlinear. They provide a better polarization exponent than the previously known kernels of the same dimensions. In particular, nonlinear kernels of dimensions 14, 15, and 16 are constructed and are shown to have optimal asymptotic error-correction performance. The optimality is proved by showing that the exponents of these kernels achieve a new upper bound that is developed in this paper. [ABSTRACT FROM AUTHOR]

Linear codes over $\mathbb {Z}_{p^{s}}$ of length $n$ are subgroups of $\mathbb {Z}_{p^{s}}^{n}$. These codes are also called $\mathbb {Z}_{p^{s}}$ -additive codes and can be seen as a generalization of linear codes over $\mathbb {Z}_{2}$ and $\mathbb {Z}_{4}$. A $\mathbb {Z}_{p^{s}}$ -linear code is a code over $\mathbb {Z}_{p}$ , not necessarily linear, which is the generalized Gray map image of a $\mathbb {Z}_{p^{s}}$ -additive code. In 2015, a systematic encoding was found for $\mathbb {Z}_{4}$ -linear codes. Moreover, an alternative permutation decoding method, which is suitable for any binary code (not necessarily linear) with a systematic encoding, was established. In this paper, we generalize these results by presenting a systematic encoding for any $\mathbb {Z}_{p^{s}}$ -linear code with $s\geq 2$ and $p$ prime. We also describe a permutation decoding method for any systematic code over $\mathbb {Z}_{p}$ , not necessarily linear, and show some examples of how to use this systematic encoding in this decoding method. [ABSTRACT FROM AUTHOR]

Binary almost instantaneous fixed-to-variable length (AIFV) codes are lossless codes that generalize the class of instantaneous fixed-to-variable length codes. The code uses two code trees and assigns source symbols to incomplete internal nodes as well as to leaves. AIFV codes are empirically shown to attain better compression ratio than Huffman codes. Nevertheless, an upper bound on the redundancy of optimal binary AIFV codes is only known to be 1, which is the same as the bound of Huffman codes. In this paper, the upper bound is improved to 1/2, which is shown to coincide with the worst-case redundancy of the codes. Along with this, the worst-case redundancy is derived for sources with p\max \geq 1 /2, where p\max is the probability of the most likely source symbol. In addition, we propose an extension of binary AIFV codes, which use $m$ code trees and allow at most $m$ -bit decoding delay. We show that the worst-case redundancy of the extended binary AIFV codes is $1/m$ for $m \leq 4$ . [ABSTRACT FROM AUTHOR]

The noise model of deletions poses significant challenges in coding theory, with basic questions like the capacity of the binary deletion channel still being open. In this paper, we study the harder model of worst case deletions, with a focus on constructing efficiently decodable codes for the two extreme regimes of high-noise and high-rate. Specifically, we construct polynomial-time decodable codes with the following tradeoffs (for any \varepsilon > 0 ): 1) codes that can correct a fraction 1- \varepsilon of deletions with rate \mathop \mathrm poly\nolimits ( \varepsilon ) over an alphabet of size \mathop \mathrm poly\nolimits (1/ \varepsilon ) ; 2) binary codes of rate 1-\tilde O(\sqrt \varepsilon ) that can correct a fraction $ \varepsilon $ of deletions; and 3) Binary codes that can be list-decoded from a fraction (1/2- \varepsilon )$ of deletions with rate \mathop {\mathrm {poly}}\nolimits ( \varepsilon ) . This paper gives the first efficient constructions which meet the qualitative goals of correcting a deletion fraction approaching 1 over bounded alphabets, and correcting a constant fraction of bit deletions with rate approaching 1 over a fixed alphabet. The above-mentioned results bring our understanding of deletion code constructions in these regimes to a similar level as worst case errors. [ABSTRACT FROM PUBLISHER]

In this paper, we consider the list decoding property of codes under insertion and deletion errors (insdel for short). Firstly, we analyse the list decodability of random insdel codes. Our result provides a more complete picture on the list decodability of insdel codes when both insertion and deletion errors happen. Secondly, we construct a family of insdel codes along with their efficient encoding and decoding algorithms through concatenation method which provides a Zyablov-type bound for insdel metric codes. [ABSTRACT FROM AUTHOR]

The goal of this paper is to present constructions of high-rate nonbinary write-once memory (WOM) codes for multilevel flash memories. The constructions provided here are all based on the basic idea of mapping high-rate binary codebooks to nonbinary codebooks. The proposed codes maintain the same length and encoding complexity as their underlying binary constituents. We begin by presenting some elementary, yet rate-efficient constructions. Afterward, we consider a high-rate two-write WOM-code defined over an alphabet of size four. In addition, we consider the application of our constructions to the creation of fixed-rate WOM codes. The constructions presented in this paper improve upon the best-known code constructions for certain code lengths. [ABSTRACT FROM AUTHOR]

One of the most important open problems in the theory of error-correcting codes is to determine the tradeoff between the rate $R$ and minimum distance $\delta $ of a binary code. The best known tradeoff is the Gilbert–Varshamov bound, and says that for every $\delta \in (0, 1/2)$ , there are codes with minimum distance $\delta $ and rate $R = {R_{\mathsf {GV}}}(\delta) > 0$ (for a certain simple function ${R_{\mathsf {GV}}}(\cdot)$ ). In this paper, we show that the Gilbert–Varshamov bound can be achieved by codes, which support local error-detection and error-correction algorithms. Specifically, we show the following results. 1) Local testing: for all $\delta \in (0,1/2)$ and all $R < {R_{\mathsf {GV}}}(\delta)$ , there exist codes with length $n$ , rate $R$ , and minimum distance $\delta $ that are locally testable with $\mathsf {quasipolylog}(n)$ query complexity. 2) Local correction: for all $\epsilon > 0$ , for all $\delta < 1/2$ sufficiently large, and all $R < (1-\epsilon) {R_{\mathsf {GV}}}(\delta)$ , there exist codes with length $n$ , rate $R$ , and minimum distance $\delta $ that are locally correctable from $({\delta }/{2}) - o(1)$ fraction errors with $O(n^{\epsilon })$ query complexity. Furthermore, these codes have an efficient randomized construction, and the local testing and local correction algorithms can be made to run in time polynomial in the query complexity. Our results on locally correctable codes also immediately give locally decodable codes with the same parameters. Our local testing result is obtained by combining Thommesen’s random concatenation technique and the best known locally testable codes by Kopparty et al. Our local correction result, which is significantly more involved, also uses random concatenation, along with a number of further ideas: the Guruswami–Sudan–Indyk list decoding strategy for concatenated codes, Alon–Edmonds–Luby distance amplification, and the local list-decodability, local list-recoverability, and local testability of Reed–Muller codes. Curiously, our final local correction algorithms go via local list-decoding and local testing algorithms; this seems to be the first time local testability is used in the construction of a locally correctable code. [ABSTRACT FROM AUTHOR]

Already in the 1960s, Levenshtein and others studied error-correcting codes that protect against synchronization errors, such as symbol insertions and deletions. However, despite significant efforts, progress on designing such codes has been lagging until recently, particularly compared to the detailed understanding of error-correcting codes for symbol substitution or erasure errors. This paper surveys the recent progress in designing efficient error-correcting codes over finite alphabets that can correct a constant fraction of worst-case insertions and deletions. Most state-of-the-art results for such codes rely on synchronization strings, simple yet powerful pseudo-random objects that have proven to be very effective solutions for coping with synchronization errors in various settings. This survey also includes an overview of what is known about synchronization strings and discusses communication settings related to error-correcting codes in which synchronization strings have been applied. [ABSTRACT FROM AUTHOR]

Projective Reed–Muller codes were introduced by Lachaud in 1988 and their dimension and minimum distance were determined by Serre and Sørensen in 1991. In coding theory, one is also interested in the higher Hamming weights, to study the code performance. Yet, not many values of the higher Hamming weights are known for these codes, not even the second lowest weight (also known as the next-to-minimal weight) is completely determined. In this paper, we determine all the values of the next-to-minimal weight for the binary projective Reed–Muller codes, which we show to be equal to the next-to-minimal weight of Reed–Muller codes in most, but not all, cases. [ABSTRACT FROM PUBLISHER]

In this paper we study array-based codes over graphs for correcting multiple node failures. These codes have applications to neural networks, associative memories, and distributed storage systems. We assume that the information is stored on the edges of a complete undirected graph and a node failure is the event where all the edges in the neighborhood of a given node have been erased. A code over graphs is called $\rho $ -node-erasure-correcting if it allows to reconstruct the erased edges upon the failure of any $\rho $ nodes or less. We present a binary optimal construction for double-node-erasure correction together with an efficient decoding algorithm, when the number of nodes is a prime number. Furthermore, we extend this construction for triple-node-erasure-correcting codes when the number of nodes is a prime number and two is a primitive element in $\mathbb {Z}_{n}$. These codes are at most a single bit away from optimality. [ABSTRACT FROM AUTHOR]

Line codes make it possible to mitigate interference, to prevent short pulses, and to generate streams of bipolar signals with no direct-current (DC) power content through balancing. They find application in magnetic recording (MR) devices, in Flash devices, in optical recording devices, and in some computer standards. This paper introduces a new family of fixed-length, binary constrained codes, named lexicographically-ordered constrained codes (LOCO codes), for bipolar non-return-to-zero signaling. LOCO codes are capacity-achieving, the lexicographic indexing enables simple, practical encoding and decoding, and this simplicity is demonstrated through analysis of circuit complexity. LOCO codes are easy to balance, and their inherent symmetry minimizes the rate loss with respect to unbalanced codes having the same constraints. Furthermore, LOCO codes that forbid certain patterns can be used to alleviate inter-symbol interference in MR systems and inter-cell interference in Flash systems. Numerical results demonstrate a gain of up to 10% in rate achieved by LOCO codes with respect to other practical constrained codes, including run-length-limited codes, designed for the same purpose. Simulation results suggest that it is possible to achieve a channel density gain of about 20% in MR systems by using a LOCO code to encode only the parity bits, limiting the rate loss, of a low-density parity-check code before writing. [ABSTRACT FROM AUTHOR]

Most bounds on the size of codes hold for any code, whether linear or not. Notably, the Griesmer bound holds only in the linear case and so optimal linear codes are not necessarily optimal codes. In this paper, we identify code parameters $(q,d,k)$ , namely, field size, minimum distance, and combinatorial dimension, for which the Griesmer bound also holds in the (systematic) nonlinear case. Moreover, we show that the Griesmer bound does not necessarily hold for a systematic code by explicit construction of a family of optimal systematic binary codes. On the other hand, we are able to provide some versions of the Griesmer bound holding for all the systematic codes. [ABSTRACT FROM AUTHOR]

We construct error-correcting write-once memory (WOM) codes that guarantee correction of any specified number of errors in $q$ -level memories. The constructions use suitably designed short $q$ -ary WOM codes and concatenate them with outer error-correcting codes over different alphabets using suitably designed mappings. With a new storage-efficiency measure, we call EC-rate and show that for common error types the codes save redundancy and implementation complexity over straightforward concatenation. In addition to constructions for guaranteed error correction, we extend the error-correcting WOM scheme to binary multi-level coding for random errors, and toward soft-decision decoding provide an efficient way to extract reliability information without using higher-precision readout. [ABSTRACT FROM AUTHOR]

In this paper, we study the close relationship between Reed–Muller codes and single-qubit phase gates from the perspective of $T$ -count optimization. We prove that minimizing the number of $T$ gates in an $n$ -qubit quantum circuit over CNOT and $T$ , together with the Clifford group powers of $T$ , corresponds to finding a minimum distance decoding of a length $2^{n}-1$ binary vector in the order $n-4$ punctured Reed–Muller code. Moreover, we show that the problems are polynomially equivalent in the length of the code. As a consequence, we derive an algorithm for the optimization of $T$ -count in quantum circuits based on Reed–Muller decoders, along with a new upper bound of $O(n^{2})$ on the number of $T$ gates required to implement an $n$ -qubit unitary over CNOT and $T$ gates. We further generalize this result to show that minimizing small angle rotations corresponds to decoding lower order binary Reed–Muller codes. In particular, we show that minimizing the number of $R_{Z}(2\pi /m)$ gates for any integer $m$ is equivalent to minimum distance decoding in $\mathcal {RM}(n-k-1, n)^{*}$ , where $k$ is the highest power of 2 dividing $m$. [ABSTRACT FROM AUTHOR]

The rate regions of multilevel diversity coding systems (MDCSs), a sub-class of the broader family of multi-source multi-sink networks with special structure, are investigated in a systematic way. We enumerate all non-isomorphic MDCS instances with at most three sources and four encoders. Then, the exact rate region of every one of these more than 7000 instances is proven via computations showing that the Shannon outer bound matches with a custom constructed linear code-based inner bound. Results gained from these computations are summarized in key statistics involving aspects, such as the sufficiency of scalar binary codes, the necessary size of vector binary codes, and so on. Also, it is shown how to construct the codes for an achievability proof. Based on this large repository of rate regions, a series of results about general MDCS cases of arbitrary size that they inspired is introduced and proved. In particular, a series of embedding operations that preserve the property of sufficiency of scalar or vector codes is presented. The utility of these operations is demonstrated by boiling the thousands of MDCS instances for which scalar binary (superposition) codes are insufficient down to 12 (26) forbidden the smallest embedded MDCS instances. [ABSTRACT FROM PUBLISHER]

In this paper, we present a fast Fourier transform algorithm over extension binary fields, where the polynomial is represented in a non-standard basis. The proposed Fourier-like transform requires \mathcal O(h\lg (h)) field operations, where h is the number of evaluation points. Based on the proposed Fourier-like algorithm, we then develop the encoding/decoding algorithms for (n=2^{m},k) Reed–Solomon erasure codes. The proposed encoding/erasure decoding algorithm requires \mathcal {O}(n\lg (n))$ , in both additive and multiplicative complexities. As the complexity leading factor is small, the proposed algorithms are advantageous in practical applications. Finally, the approaches to convert the basis between the monomial basis and the new basis are proposed. [ABSTRACT FROM AUTHOR]

Consider the problem of packing Hamming balls of a given relative radius subject to the constraint that they cover any point of the ambient Hamming space with multiplicity at most $L$ . For odd $L\ge 3$ , an asymptotic upper bound on the rate of any such packing is proved. The resulting bound improves the best known bound (due to Blinovsky’1986) for rates below a certain threshold. The method is a superposition of the linear-programming idea of Ashikhmin, Barg, and Litsyn (that was previously used to improve the estimates of Blinovsky for $L=2$ ) and a Ramsey-theoretic technique of Blinovsky. As an application, it is shown that for all odd $L$ , the slope of the rate-radius tradeoff is zero at zero rate. [ABSTRACT FROM AUTHOR]

We say that a $q$ -ary length n$ code is non-overlapping if the set of non-trivial prefixes of codewords and the set of non-trivial suffices of codewords are disjoint. These codes were first studied by Levenshtein in 1964, motivated by applications in synchronization. More recently these codes were independently invented (under the name cross-bifix-free codes) by Bajić and Stojanović. We provide a simple construction for a class of non-overlapping codes which has optimal cardinality whenever n$ divides q$ . Moreover, for all parameters n$ and q$ , we show that a code from this class is close to optimal, in the sense that it has cardinality within a constant factor of an upper bound due to Levenshtein from 1970. Previous constructions have cardinality within a constant factor of the upper bound only when q$ is fixed. Chee, Kiah, Purkayastha, and Wang showed that a codewords; this bound is weaker than the Levenshtein bound. Their proof appealed to the application in synchronization: we provide a direct combinatorial argument to establish the bound of Chee et al. We also consider codes of short length, finding the leading term of the maximal cardinality of a non-overlapping code when $n$ is fixed and $q\rightarrow \infty $ . The largest cardinality of non-overlapping codes of lengths 3 or less is determined exactly. [ABSTRACT FROM AUTHOR]

We analyze the optimal tradeoff between the error exponent and the excess-rate exponent for variable-rate Slepian–Wolf codes. In particular, we first derive upper (converse) bounds on the optimal error and excess-rate exponents, and then lower (achievable) bounds, via a simple class of variable-rate codes which assign the same rate to all source blocks of the same type class. Then, using the exponent bounds, we derive bounds on the optimal rate functions, namely, the minimal rate assigned to each type class, needed in order to achieve a given target error exponent. The resulting excess-rate exponent is then evaluated. Iterative algorithms are provided for the computation of both bounds on the optimal rate functions and their excess-rate exponents. The resulting Slepian–Wolf codes bridge between the two extremes of fixed-rate coding, which has minimal error exponent and maximal excess-rate exponent, and average-rate coding, which has maximal error exponent and minimal excess-rate exponent. [ABSTRACT FROM AUTHOR]

The construction of deletion codes for the editing metric is reduced to the construction of codes over the integers for the Manhattan metric by run length coding. The latter codes are constructed by expurgation of lattices’ translates. These lattices, in turn, are obtained from Construction A applied to binary codes and \mathbb Z4 –codes. A lower bound on the size of our codes for the Manhattan distance are obtained through generalized theta series of the corresponding lattices. For any fixed number of deletions, provided the number of runs is large enough our method supplies a correction technique. For fixed number of runs and binary sequence length large our lattice construction is shown to be tight up to constants. [ABSTRACT FROM PUBLISHER]

We show that it is possible to encode any communication protocol between two parties so that the protocol succeeds even if a \((1/4 -\epsilon )\) fraction of all symbols transmitted by the parties are corrupted adversarially, at a cost of increasing the communication in the protocol by a multiplicative factor that depends only on \(\epsilon \) , using an alphabet whose size depends only on \(\epsilon \) . This improves on an earlier result of Schulman, who showed how to recover when the fraction of errors is bounded by 1/240. We also show how to simulate an arbitrary protocol with a protocol using the binary alphabet, a constant factor increase in communication, and tolerating a \(1/8 -\epsilon \) fraction of errors. [ABSTRACT FROM PUBLISHER]

This work gives an explicit construction of a family of error correcting codes for the binary deletion channel and for the Poisson repeat channel. In the binary deletion channel with parameter $p$ (${\mathrm {BDC}}_{p}$) every bit is deleted independently with probability $p$. A lower bound of $(1-p)/9$ is known on the capacity of the ${\mathrm {BDC}}_{p}$ , yet no explicit construction is known to achieve this rate. We give an explicit family of codes of rate $(1-p)/16$ , for every $p$. This improves upon the work of Guruswami and Li (2018) that gave a construction of rate $(1-p)/120$. The codes in our family have polynomial time encoding and decoding algorithms. Another channel considered in this work is the Poisson repeat channel with parameter $\lambda $ (PRC $_{\lambda }$) in which every bit is replaced with a discrete Poisson number of copies of that bit, where the number of copies has mean $\lambda $. We show that our construction works for this channel as well. As far as we know, this is the first explicit construction of an error correcting code for PRC $_{\lambda }$. [ABSTRACT FROM AUTHOR]

In this article, we propose an adaptation of the algorithmic reduction theory of lattices to binary codes. This includes the celebrated LLL algorithm (Lenstra, Lenstra, Lovasz, 1982), as well as adaptations of associated algorithms such as the Nearest Plane Algorithm of Babai (1986). Interestingly, the adaptation of LLL to binary codes can be interpreted as an algorithmic version of the bound of Griesmer (1960) on the minimal distance of a code. Using these algorithms, we demonstrate—both with a heuristic analysis and in practice—a small polynomial speed-up over the Information-Set Decoding algorithm of Lee and Brickell (1988) for random binary codes. This appears to be the first such speed-up that is not based on a time-memory trade-off. The above speed-up should be read as a very preliminary example of the potential of a reduction theory for codes, for example in cryptanalysis. [ABSTRACT FROM AUTHOR]

A family of error-correcting codes is list-decodable from error fraction $p$ if, for every code in the family, the number of codewords in any Hamming ball of fractional radius $p$ is less than some integer $L$. It is said to be list-recoverable for input list size $\ell $ if for every sufficiently large subset of at least $L$ codewords, there is a coordinate where the codewords take more than $\ell $ values. In this work, we study the list size of random linear codes for both list-decoding and list-recovery as the rate approaches capacity. We show the following claims hold with high probability over the choice of the code (below $q$ is the alphabet size, and $ \varepsilon > 0$ is the gap to capacity). (1) A random linear code of rate $1 - \log _{q}(\ell) - \varepsilon $ requires list size $L \ge \ell ^{\Omega (1/ \varepsilon)}$ for list-recovery from input list size $\ell $. (2) A random linear code of rate $1 - h_{q}(p) - \varepsilon $ requires list size $L \ge \left \lfloor{ {h_{q}(p)/ \varepsilon +0.99}}\right \rfloor $ for list-decoding from error fraction $p$. (3) A random binary linear code of rate $1 - h_{2}(p) - \varepsilon $ is list-decodable from average error fraction $p$ with list size with $L \leq \left \lfloor{ {h_{2}(p)/ \varepsilon }}\right \rfloor + 2$. Our lower bounds follow by exhibiting an explicit subset of codewords so that this subset—or some symbol-wise permutation of it—lies in a random linear code with high probability. Our upper bound follows by strengthening a result of (Li, Wootters, 2018). [ABSTRACT FROM AUTHOR]

We give a complete answer to the following basic question: “What is the maximal fraction of deletions or insertions tolerable by $q$ -ary list-decodable codes with non-vanishing information rate?” This question has been open even for binary codes, including the restriction to the binary insertion-only setting, where the best-known result was that a $\gamma \leq 0.707$ fraction of insertions is tolerable by some binary code family. For any desired $\varepsilon > 0$ , we construct a family of binary codes of positive rate which can be efficiently list-decoded from any combination of $\gamma $ fraction of insertions and $\delta $ fraction of deletions as long as $\gamma + 2\delta \leq 1 - \varepsilon $. On the other hand, for any $\gamma, \delta $ with $\gamma + 2\delta = 1$ list-decoding is impossible. Our result thus precisely characterizes the feasibility region of binary list-decodable codes for insertions and deletions. We further generalize our result to codes over any finite alphabet of size $q$. Surprisingly, our work reveals that the feasibility region for $q>2$ is not the natural generalization of the binary bound above. We provide tight upper and lower bounds that precisely pin down the feasibility region, which turns out to have a $(q-1)$ -piece-wise linear boundary whose $q$ corner-points lie on a quadratic curve. The main technical work in our results is proving the existence of code families of sufficiently large size with good list-decoding properties for any combination of $\delta,\gamma $ within the claimed feasibility region. We achieve this via an intricate analysis of codes introduced by [Bukh and Ma, 2014]. Finally, we give a simple yet powerful concatenation scheme for list-decodable insertion-deletion codes which transforms any such (non-efficient) code family (with vanishing information rate) into an efficiently decodable code family with constant rate. [ABSTRACT FROM AUTHOR]

We give an explicit construction of length- $n$ binary codes capable of correcting the deletion of two bits that have size $2^{n}/n^{4+o(1)}$. This matches up to lower order terms the existential result, based on an inefficient greedy choice of codewords, that guarantees such codes of size $\Omega (2^{n}/n^{4})$. Our construction is based on augmenting the classic Varshamov-Tenengolts construction of single deletion codes with additional check equations. We also give an explicit construction of binary codes of size $\Omega (2^{n}/n^{3+o(1)})$ that can be list decoded from two deletions using lists of size two. Previously, even the existence of such codes was not clear. [ABSTRACT FROM AUTHOR]

Error-correcting codes that admit local decoding and correcting algorithms have been the focus of much recent research due to their numerous applications. An important goal is to obtain the best possible tradeoffs between the number of symbols of the codeword that the local decoding algorithm must examine (the locality), and the amount of redundancy in the encoding (the information rate). In Hamming’s classical adversarial channel model, the current tradeoffs are dramatic, allowing either small locality but superpolynomial blocklength, or small blocklength but high locality. However, in the computationally bounded adversarial channel model, proposed by Lipton (STACS 1994), constructions of locally decodable codes suddenly exhibit small locality and small blocklength, but these constructions require strong trusted setup assumptions. We study variants of locally decodable and locally correctable codes in computationally bounded, adversarial channels, in a setting with no trusted setup. The only assumption we require is the selection of the public parameters (seed) for a collision-resistant hash function. Specifically, we provide constructions of relaxed locally correctable and relaxed locally decodable codes over the binary alphabet, with constant information rate, and poly-logarithmic locality. Our constructions, which compare favorably with their classical analogs, crucially employ collision-resistant hash functions and local expander graphs, extending ideas from recent cryptographic constructions of memory-hard functions. [ABSTRACT FROM AUTHOR]

An indel refers to a single insertion or deletion, while an edit refers to a single insertion, deletion or substitution. In this article, we investigate codes that correct either a single indel or a single edit and provide linear-time algorithms that encode binary messages into these codes of length n. Over the quaternary alphabet, we provide two linear-time encoders. One corrects a single edit with ⌈log n⌉ + O(log log n) redundancy bits, while the other corrects a single indel with ⌈log n⌉ + 2 redundant bits. These two encoders are order-optimal. The former encoder is the first known order-optimal encoder that corrects a single edit, while the latter encoder (that corrects a single indel) reduces the redundancy of the best known encoder of Tenengolts (1984) by at least four bits. Over the DNA alphabet, we impose an additional constraint: the GC-balanced constraint and require that exactly half of the symbols of any DNA codeword to be either C or G. In particular, via a modification of Knuth’s balancing technique, we provide a linear-time map that translates binary messages into GC-balanced codewords and the resulting codebook is able to correct a single indel or a single edit. These are the first known constructions of GC-balanced codes that correct a single indel or a single edit. [ABSTRACT FROM AUTHOR]

There has been a great deal of work establishing that random linear codes are as list-decodable as uniformly random codes, in the sense that a random linear binary code of rate $1 - {H}(\text {p}) - \epsilon $ is $({p},\text {O}(1/\epsilon))$ -list-decodable with high probability. In this work, we show that such codes are $({p}, {H}({p})/\epsilon + 2)$ -list-decodable with high probability, for any $ {p} \in (0, 1/2)$ and $\epsilon > 0$. In addition to improving the constant in known list-size bounds, our argument—which is quite simple—works simultaneously for all values of p, while previous works obtaining $ {L} = \text {O}(1/\epsilon)$ patched together different arguments to cover different parameter regimes. Our approach is to strengthen an existential argument of (Guruswami, Håstad, Sudan and Zuckerman, IEEE Trans. IT, 2002) to hold with high probability. To complement our upper bound for random linear codes, we also improve an argument of (Guruswami, Narayanan, IEEE Trans. IT, 2014) to obtain an essentially tight lower bound of $1/\epsilon $ on the list size of uniformly random codes; this implies that random linear codes are in fact more list-decodable than uniformly random codes, in the sense that the list sizes are strictly smaller. To demonstrate the applicability of these techniques, we use them to (a) obtain more information about the distribution of list sizes of random linear codes and (b) to prove a similar result for random linear rank-metric codes. [ABSTRACT FROM AUTHOR]

The explosion in the volumes of data being stored online has resulted in distributed storage ‘s transitioning to erasure coding based schemes. Local Reconstruction Codes (LRCs) have emerged as the codes of choice for these applications. These codes can correct a small number of erasures (which is the typical case) by accessing only a small number of remaining coordinates. An $(n,r,h,a,q)$ -LRC is a linear code over $\mathbb {F}_{q}$ of length $n$ , whose codeword symbols are partitioned into $g=n/r$ local groups each of size $r$. Each local group has $a$ local parity checks that allow recovery of up to $a$ erasures within the group by reading the unerased symbols in the group. There are a further $h$ “heavy” parity checks to provide fault tolerance from more global erasure patterns. Such an LRC is Maximally Recoverable (MR), if it corrects all erasure patterns which are information-theoretically correctable under the stipulated structure of local and global parity checks, namely patterns with up to $a$ erasures in each local group and an additional $h$ (or fewer) erasures anywhere in the codeword. The existing constructions require fields of size $n^{\Omega (h)}$ while no superlinear lower bounds were known for any setting of parameters. Is it possible to get linear field size similar to the related MDS codes (e.g., Reed-Solomon codes)? In this work, we answer this question by showing superlinear lower bounds on the field size of MR-LRCs. When $a,h$ are constant and the number of local groups $g \geqslant h$ , while $r$ may grow with $n$ , our lower bound simplifies to $q \geqslant \Omega _{a,h}\left ({n\cdot r^{\min \{a,h-2\}}}\right)$. MR-LRCs deployed in practice have a small number of global parities, typically $h=2,3$. We complement our lower bounds by giving constructions with small field size for $h \leqslant 3$. When $h=2$ , we give a linear field size construction, whereas previous constructions required quadratic field size in some parameter ranges. Note that our lower bound is superlinear only if $h \geqslant 3$. When $h=3$ , we give a construction with $O(n^{3})$ field size, whereas previous constructions needed $n^{\Theta (a)}$ field size. This makes the choices $r=3, a=1, h=3$ the next simplest non-trivial setting to investigate regarding the existence of MR-LRCs over fields of near-linear size. We answer this question in the positive via a novel approach based on elliptic curves and arithmetic progression free sets. [ABSTRACT FROM AUTHOR]

A tiling of $\mathbb {F}_{2}^{n}$ (considered as a graph) gives rise to a perfect code (according to a given metric) if the basic tile is a metric ball. We are concerned with metrics on $\mathbb {F}_{2}^{n}$ that are determined by a weight which respects the support of vectors (TS-metrics) and in this case, a perfect code is called TS-perfect. We consider all the tilings of $\mathbb {F}_{2}^{n}$ by tiles with up to 8 elements (which are classified in the literature) and determine which of them give rise to a TS-perfect code. In the sequence, for those tilings that give rise to a perfect code for some TS-metric, we classify the TS-metrics (up to equivalence) that turn it into a perfect code. Also, we give a general construction to obtain TS-perfect codes out of given TS-perfect codes, by proving that concatenation of two TS-perfect codes is by itself a TS-perfect code. [ABSTRACT FROM AUTHOR]

In this work, we study the problem of list decoding of insertions and deletions. We present a Johnson-type upper bound on the maximum list size. The bound is meaningful only when insertions occur. Our bound implies that there are binary codes of rate $\Omega (1)$ that are list-decodable from a 0.707-fraction of insertions. For any $\tau _{\mathsf {I}} \geq 0$ and $\tau _{\mathsf {D}} \in [0,1)$ , there exist $q$ -ary codes of rate $\Omega (1)$ that are list-decodable from a $\tau _{\mathsf {I}}$ -fraction of insertions and $\tau _{\mathsf {D}}$ -fraction of deletions, where $q$ depends only on $\tau _{\mathsf {I}}$ and $\tau _{\mathsf {D}}$. We also provide efficient encoding and decoding algorithms for list-decoding from $\tau _{\mathsf {I}}$ -fraction of insertions and $\tau _{\mathsf {D}}$ -fraction of deletions for any $\tau _{\mathsf {I}} \geq 0$ and $\tau _{\mathsf {D}} \in [0,1)$. Based on the Johnson-type bound, we derive a Plotkin-type upper bound on the code size in the Levenshtein metric. [ABSTRACT FROM AUTHOR]

A transmitter observing a sequence of independent and identically distributed random variables seeks to keep a receiver updated about its latest observations. The receiver need not be apprised about each symbol seen by the transmitter, but needs to output a symbol at each time instant $t$. If at time $t$ the receiver outputs the symbol seen by the transmitter at time $U(t)\leq t$ , the age of information at the receiver at time $t$ is $t-U(t)$. We study the design of lossless source codes that enable transmission with minimum average age at the receiver. We show that the asymptotic minimum average age can be attained up to a constant gap by the Shannon codes for a tilted version of the original pmf generating the symbols, which can be computed easily by solving an optimization problem. Furthermore, we exhibit an example with alphabet $\mathcal {X}$ where Shannon codes for the original pmf incur an asymptotic average age of a factor $O(\sqrt {\log | \mathcal {X}|})$ more than that achieved by our codes. Underlying our prescription for optimal codes is a new variational formula for integer moments of random variables, which may be of independent interest. Also, we discuss possible extensions of our formulation to randomized schemes and to the erasure channel, and include a treatment of the related problem of source coding for minimum average queuing delay. [ABSTRACT FROM AUTHOR]

Erasure codes play an important role in storage systems to prevent data loss. In this work, we study a class of erasure codes called Multi-Erasure Locally Recoverable Codes (ME-LRCs) for storage arrays. Compared to previous related works, we focus on the construction of ME-LRCs over small fields. Our main contribution is a general construction of ME-LRCs based on generalized tensor product codes, and an analysis of their erasure-correcting properties. A decoding algorithm tailored for erasure recovery is given, and correctable erasure patterns are identified. We then prove that our construction yields optimal ME-LRCs with a wide range of code parameters, and present some explicit ME-LRCs over small fields. Next, we show that generalized integrated interleaving (GII) codes can be treated as a subclass of generalized tensor product codes, thus defining the exact relation between these codes. Finally, ME-LRCs are investigated in a probabilistic setting. We prove that ME-LRCs based upon a generalized tensor product construction can achieve the capacity of a compound erasure channel consisting of a family of erasure product channels. [ABSTRACT FROM AUTHOR]

Locally repairable codes (LRCs) are considered with equal or unequal localities, local distances, and local field sizes. An explicit two-layer architecture with a sum-rank outer code is obtained, having disjoint local groups and achieving maximal recoverability (MR) for all families of local linear codes (MDS or not) simultaneously, up to a specified maximum locality $r $. Furthermore, the local linear codes (thus the localities, local distances, and local fields) can be efficiently and dynamically modified without global recoding or changes in architecture or outer code, while preserving the MR property, easily adapting to new configurations in storage or new hot and cold data. In addition, local groups and file components can be added, removed or updated without global recoding. The construction requires global fields of size roughly $g^{r} $ , for $g $ local groups and maximum or specified locality $r $. For equal localities, these global fields are smaller than those of previous MR-LRCs when $r \leq h $ (global parities). For unequal localities, they provide an exponential field size reduction on all previous best known MR-LRCs. For bounded localities and a large number of local groups, the global erasure-correction complexity of the given construction is comparable to that of Tamo–Barg codes or Reed–Solomon codes with local replication, while local repair is as efficient as for the Cartesian product of the local codes. Reed–Solomon codes with local replication and Cartesian products are recovered from the given construction when $r=1 $ and $h = 0 $ , respectively. The given construction can also be adapted to provide hierarchical MR-LRCs for all types of hierarchies and parameters. Finally, subextension subcodes and sum-rank alternant codes are introduced to obtain further exponential field size reductions, at the expense of lower information rates. [ABSTRACT FROM AUTHOR]

In the random deletion channel, each bit is deleted independently with probability $p$. For the random deletion channel, the existence of codes of rate $(1-p)/9$ , and thus bounded away from 0 for any $p < 1$ , has been known. We give an explicit construction with polynomial time encoding and deletion correction algorithms with rate $c_{0} (1-p)$ for an absolute constant $c_{0} > 0$. [ABSTRACT FROM AUTHOR]

It is known that, for large user word lengths, the auxiliary data can be used to recover most of the redundancy losses of Knuth’s simple balancing method compared with the optimal redundancy of balanced codes for the binary case. Here, this important result is extended in a number of ways. First, an upper bound for the amount of auxiliary data is derived that is valid for all codeword lengths. This result is primarily of theoretical interest, as it defines the probability distribution of the number of balancing indices that results in optimal redundancy. This result is equally valid for particular non-binary generalizations of Knuth’s balancing method. Second, an asymptotically exact expression for the amount of auxiliary data for the ternary case of a variable length realization of the modified balanced code construction is derived, that, in all respects, is the analogue of the result obtained for the binary case. The derivation is based on a generalization of the binary random walk to the ternary case and a simple modification of an existing generalization of Knuth’s method for the non-binary balanced codes. Finally, a conjecture is proposed regarding the probability distribution of the number of balancing indices for any alphabet size. [ABSTRACT FROM AUTHOR]

A general criterion to obtain $s$ -PD-sets of minimum size $s+1$ for partial permutation decoding, which enable correction up to $s$ errors, for systematic codes over a finite field ${ {F}}_{q}$ and ${ {Z}}_{4}$ -linear codes is provided. We show how this technique can be easily applied to linear cyclic codes over ${ {F}}_{q}$ , ${ {Z}}_{4}$ -linear codes which are the Gray map image of a quaternary linear cyclic code, and some related codes such as quasi-cyclic codes. Furthermore, specific results for some linear and nonlinear binary codes, including simplex, Kerdock, Delsarte-Goethals, and extended dualized Kerdock codes are given. Finally, applying this technique, new $s$ -PD-sets of size $s+1$ for ${ {Z}}_{4}$ -linear Hadamard codes of type $2^\gamma 4^\delta $ , for all $\delta \geq 4$ and $1< s\leq 2^\delta -3$ ; and for ${ {Z}}_{4}$ -linear simplex codes of type $4^{m}$ , for all $m\geq 2$ and $1< s\leq 2^{m+1}-3$ , are also provided. [ABSTRACT FROM AUTHOR]

We consider the problem of constructing binary codes to recover from k –bit deletions with efficient encoding/decoding, for a fixed k . The single deletion case is well understood, with the Varshamov–Tenengolts–Levenshtein code from 1965 giving an asymptotically optimal construction with \approx ~2^n/n codewords of length n , i.e., at most \log n bits of redundancy. However, even for the case of two deletions, there was no known explicit construction with redundancy less than n^{\Omega (1)} . For any fixed k , we construct a binary code with ck \log n redundancy that can be decoded from k deletions in Ok(n \log ^{4} n) time. The coefficient ck can be taken to be O(k^2 \log k) , which is only quadratically worse than the optimal, non-constructive bound of $O(k)$ . We also indicate how to modify this code to allow for a combination of up to $k$ insertions and deletions. We also note that among linear codes capable of correcting $k$ deletions, the $(k+1)$ -fold repetition code is essentially the best possible. [ABSTRACT FROM PUBLISHER]

We consider codes over fixed alphabets against worst case symbol deletions. For any fixed k \ge 2 , we construct a family of codes over alphabet of size k with positive rate, which allow efficient recovery from a worst case deletion fraction approaching 1-(2/(k+\sqrt k)) . In particular, for binary codes, we are able to recover a fraction of deletions approaching 1/(\sqrt 2 +1)=\sqrt 2-1 \approx 0.414 . Previously, even non-constructively, the largest deletion fraction known to be correctable with positive rate was 1-\Theta (1/\sqrt k) , and around 0.17 for the binary case. Our result pins down the largest fraction of correctable deletions for $k$ -ary codes as 1-\Theta (1/k)$ , since 1-1/k$ is an upper bound even for the simpler model of erasures where the locations of the missing symbols are known. Closing the gap between and 1/2 for the limit of worst case deletions correctable by binary codes remains a tantalizing open question. [ABSTRACT FROM PUBLISHER]

We generalize Helberg’s number-theoretic construction of binary multiple insertion/deletion correcting codes to non-binary alphabets and describe a linear decoding algorithm for correcting multiple deletions. [ABSTRACT FROM AUTHOR]

We propose almost instantaneous fixed-to-variable length (AIFV) codes such that two (resp. $K-1$ ) code trees are used, if code symbols are binary (resp. $K$ -ary for $K\geq 3$ ), and source symbols are assigned to incomplete internal nodes in addition to leaves. Although the AIFV codes are not instantaneous codes, they are devised such that the decoding delay is at most two bits (resp. one code symbol) in the case of binary (resp. $K$ -ary) code alphabet. The AIFV code can attain better average compression rate than the Huffman code at the expenses of a little decoding delay and a little large memory size to store multiple code trees. We also show for the binary and ternary AIFV codes that the optimal AIFV code can be obtained by solving 0-1 integer programming problems. [ABSTRACT FROM AUTHOR]