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Alexander Vardy

Publications and source records attributed to Alexander Vardy.

66 records · Page 4Linked to original sources

A Nearly Optimal Construction of Flash Codes

Flash memory is a non-volatile computer memory comprised of blocks of cells, wherein each cell can take on q different values or levels. While increasing the cell level is easy, reducing the level of a cell can be accomplished only by erasing an entire block. Since block erasures are highly undesirable, coding schemes - known as floating codes or flash codes - have been designed in order to maximize the number of times that information stored in a flash memory can be written (and re-written) prior to incurring a block erasure. An (n,k,t)_q flash code C is a coding scheme for storing k information bits in n cells in such a way that any sequence of up to t writes (where a write is a transition 0 -> 1 or 1 -> 0 in any one of the k bits) can be accommodated without a block erasure. The total number of available level transitions in n cells is n(q-1), and the write deficiency of C, defined as δ(C) = n(q-1) - t, is a measure of how close the code comes to perfectly utilizing all these transitions. For k > 6 and large n, the best previously known construction of flash codes achieves a write deficiency of O(qk^2). On the other hand, the best known lower bound on write deficiency is Ω(qk). In this paper, we present a new construction of flash codes that approaches this lower bound to within a factor logarithmic in k. To this end, we first improve upon the so-called "indexed" flash codes, due to Jiang and Bruck, by eliminating the need for index cells in the Jiang-Bruck construction. Next, we further increase the number of writes by introducing a new multi-stage (recursive) indexing scheme. We then show that the write deficiency of the resulting flash codes is O(qk\log k) if q \geq \log_2k, and at most O(k\log^2 k) otherwise.

cs.IT↗

Multidimensional Flash Codes

Flash memory is a non-volatile computer memory comprised of blocks of cells, wherein each cell can take on q different levels corresponding to the number of electrons it contains. Increasing the cell level is easy; however, reducing a cell level forces all the other cells in the same block to be erased. This erasing operation is undesirable and therefore has to be used as infrequently as possible. We consider the problem of designing codes for this purpose, where k bits are stored using a block of n cells with q levels each. The goal is to maximize the number of bit writes before an erase operation is required. We present an efficient construction of codes that can store an arbitrary number of bits. Our construction can be viewed as an extension to multiple dimensions of the earlier work of Jiang and Bruck, where single-dimensional codes that can store only 2 bits were proposed.

cs.IT↗

Analog Codes on Graphs

We consider the problem of transmission of a sequence of real data produced by a Nyquist sampled band-limited analog source over a band-limited analog channel, which introduces an additive white Gaussian noise. An analog coding scheme is described, which can achieve a mean-squared error distortion proportional to $(1+SNR)^{-B}$ for a bandwidth expansion factor of $B/R$, where $0 < R < 1$ is the rate of individual component binary codes used in the construction and $B \geq 1$ is an integer. Thus, over a wide range of SNR values, the proposed code performs much better than any single previously known analog coding system.

cs.IT↗

On an Improvement over Rényi's Equivocation Bound

We consider the problem of estimating the probability of error in multi-hypothesis testing when MAP criterion is used. This probability, which is also known as the Bayes risk is an important measure in many communication and information theory problems. In general, the exact Bayes risk can be difficult to obtain. Many upper and lower bounds are known in literature. One such upper bound is the equivocation bound due to Rényi which is of great philosophical interest because it connects the Bayes risk to conditional entropy. Here we give a simple derivation for an improved equivocation bound. We then give some typical examples of problems where these bounds can be of use. We first consider a binary hypothesis testing problem for which the exact Bayes risk is difficult to derive. In such problems bounds are of interest. Furthermore using the bounds on Bayes risk derived in the paper and a random coding argument, we prove a lower bound on equivocation valid for most random codes over memoryless channels.

cs.IT↗

On the Stopping Distance and the Stopping Redundancy of Codes

It is now well known that the performance of a linear code $C$ under iterative decoding on a binary erasure channel (and other channels) is determined by the size of the smallest stopping set in the Tanner graph for $C$. Several recent papers refer to this parameter as the \emph{stopping distance} $s$ of $C$. This is somewhat of a misnomer since the size of the smallest stopping set in the Tanner graph for $C$ depends on the corresponding choice of a parity-check matrix. It is easy to see that $s \le d$, where $d$ is the minimum Hamming distance of $C$, and we show that it is always possible to choose a parity-check matrix for $C$ (with sufficiently many dependent rows) such that $s = d$. We thus introduce a new parameter, termed the \emph{stopping redundancy} of $C$, defined as the minimum number of rows in a parity-check matrix $H$ for $C$ such that the corresponding stopping distance $s(H)$ attains its largest possible value, namely $s(H) = d$. We then derive general bounds on the stopping redundancy of linear codes. We also examine several simple ways of constructing codes from other codes, and study the effect of these constructions on the stopping redundancy. Specifically, for the family of binary Reed-Muller codes (of all orders), we prove that their stopping redundancy is at most a constant times their conventional redundancy. We show that the stopping redundancies of the binary and ternary extended Golay codes are at most 35 and 22, respectively. Finally, we provide upper and lower bounds on the stopping redundancy of MDS codes.

cs.IT↗

Coding for the Optical Channel: the Ghost-Pulse Constraint

We consider a number of constrained coding techniques that can be used to mitigate a nonlinear effect in the optical fiber channel that causes the formation of spurious pulses, called ``ghost pulses.'' Specifically, if $b_1 b_2 ... b_{n}$ is a sequence of bits sent across an optical channel, such that $b_k=b_l=b_m=1$ for some $k,l,m$ (not necessarily all distinct) but $b_{k+l-m} = 0$, then the ghost-pulse effect causes $b_{k+l-m}$ to change to 1, thereby creating an error. We design and analyze several coding schemes using binary and ternary sequences constrained so as to avoid patterns that give rise to ghost pulses. We also discuss the design of encoders and decoders for these coding schemes.

cs.IT↗

On the Asymptotic Performance of Iterative Decoders for Product Codes

We consider hard-decision iterative decoders for product codes over the erasure channel, which employ repeated rounds of decoding rows and columns alternatingly. We derive the exact asymptotic probability of decoding failure as a function of the error-correction capabilities of the row and column codes, the number of decoding rounds, and the channel erasure probability. We examine both the case of codes capable of correcting a constant amount of errors, and the case of codes capable of correcting a constant fraction of their length.

cs.IT↗

Duality between Packings and Coverings of the Hamming Space

We investigate the packing and covering densities of linear and nonlinear binary codes, and establish a number of duality relationships between the packing and covering problems. Specifically, we prove that if almost all codes (in the class of linear or nonlinear codes) are good packings, then only a vanishing fraction of codes are good coverings, and vice versa: if almost all codes are good coverings, then at most a vanishing fraction of codes are good packings. We also show that any specific maximal binary code is either a good packing or a good covering, in a certain well-defined sense.

cs.IT↗

Optimal Tristance Anticodes in Certain Graphs

For $z_1,z_2,z_3 \in \Z^n$, the \emph{tristance} $d_3(z_1,z_2,z_3)$ is a generalization of the $L_1$-distance on $\Z^n$ to a quantity that reflects the relative dispersion of three points rather than two. A tristance anticode $\cA_d$ of diameter $d$ is a subset of $\Z^n$ with the property that $d_3(z_1,z_2,z_3) \leq d$ for all $z_1,z_2,z_3 \in \cA_d$. An anticode is optimal if it has the largest possible cardinality for its diameter $d$. We determine the cardinality and completely classify the optimal tristance anticodes in $\Z^2$ for all diameters $d \ge 1$. We then generalize this result to two related distance models: a different distance structure on $\Z^2$ where $d(z_1,z_2) = 1$ if $z_1,z_2$ are adjacent either horizontally, vertically, or diagonally, and the distance structure obtained when $\Z^2$ is replaced by the hexagonal lattice $A_2$. We also investigate optimal tristance anticodes in $\Z^3$ and optimal quadristance anticodes in $\Z^2$, and provide bounds on their cardinality. We conclude with a brief discussion of the applications of our results to multi-dimensional interleaving schemes and to connectivity loci in the game of Go.

math.CO↗

Maximum-likelihood decoding of Reed-Solomon Codes is NP-hard

Maximum-likelihood decoding is one of the central algorithmic problems in coding theory. It has been known for over 25 years that maximum-likelihood decoding of general linear codes is NP-hard. Nevertheless, it was so far unknown whether maximum- likelihood decoding remains hard for any specific family of codes with nontrivial algebraic structure. In this paper, we prove that maximum-likelihood decoding is NP-hard for the family of Reed-Solomon codes. We moreover show that maximum-likelihood decoding of Reed-Solomon codes remains hard even with unlimited preprocessing, thereby strengthening a result of Bruck and Naor.

cs.CC↗

Asymptotic Improvement of the Gilbert-Varshamov Bound on the Size of Binary Codes

Given positive integers $n$ and $d$, let $A_2(n,d)$ denote the maximum size of a binary code of length $n$ and minimum distance $d$. The well-known Gilbert-Varshamov bound asserts that $A_2(n,d) \geq 2^n/V(n,d-1)$, where $V(n,d) = \sum_{i=0}^{d} {n \choose i}$ is the volume of a Hamming sphere of radius $d$. We show that, in fact, there exists a positive constant $c$ such that $$ A_2(n,d) \geq c \frac{2^n}{V(n,d-1)} \log_2 V(n,d-1) $$ whenever $d/n \le 0.499$. The result follows by recasting the Gilbert- Varshamov bound into a graph-theoretic framework and using the fact that the corresponding graph is locally sparse. Generalizations and extensions of this result are briefly discussed.

math.CO↗

A Lower Bound on the Density of Sphere Packings via Graph Theory

Using graph-theoretic methods we give a new proof that for all sufficiently large $n$, there exist sphere packings in $\R^n$ of density at least $cn2^{-n}$, exceeding the classical Minkowski bound by a factor linear in $n$. This matches up to a constant the best known lower bounds on the density of sphere packings due to Rogers, Davenport-Rogers, and Ball. The suggested method makes it possible to describe the points of such a packing with complexity $\exp(n\log n)$, which is significantly lower than in the other approaches.

math.CO↗