18,392 research outputs found
On a Class of Optimal Nonbinary Linear Unequal-Error-Protection Codes for Two Sets of Messages
Several authors have addressed the problem of designing good linear unequal error protection (LUEP) codes. However, very little is known about good nonbinary LUEP codes. We present a class of optimal nonbinary LUEP codes for two different sets of messages. By combining t-error-correcting ReedSolomon (RS) codes and shortened nonbinary Hamming codes, we obtain nonbinary LUEP codes that protect one set of messages against any t or fewer symbol errors and the remaining set of messages against any single symbol error. For t ≥ 2, we show that these codes are optimal in the sense of achieving the Hamming lower bound on the number of redundant symbols of a nonbinary LUEP code with the same parameters
Subspace subcodes of Reed-Solomon codes
We introduce a class of nonlinear cyclic error-correcting codes, which we call subspace subcodes of Reed-Solomon (SSRS) codes. An SSRS code is a subset of a parent Reed-Solomon (RS) code consisting of the RS codewords whose components all lie in a fixed ν-dimensional vector subspace S of GF (2m). SSRS codes are constructed using properties of the Galois field GF(2m). They are not linear over the field GF(2ν), which does not come into play, but rather are Abelian group codes over S. However, they are linear over GF(2), and the symbol-wise cyclic shift of any codeword is also a codeword. Our main result is an explicit but complicated formula for the dimension of an SSRS code. It implies a simple lower bound, which gives the true value of the dimension for most, though not all, subspaces. We also prove several important duality properties. We present some numerical examples, which show, among other things, that (1) SSRS codes can have a higher dimension than comparable subfield subcodes of RS codes, so that even if GF(2ν) is a subfield of GF(2m), it may not be the best ν-dimensional subspace for constructing SSRS codes; and (2) many high-rate SSRS codes have a larger dimension than any previously known code with the same values of n, d, and q, including algebraic-geometry codes. These examples suggest that high-rate SSRS codes are promising candidates to replace Reed-Solomon codes in high-performance transmission and storage systems
Trellis decoding complexity of linear block codes
In this partially tutorial paper, we examine minimal trellis representations of linear block codes and analyze several measures of trellis complexity: maximum state and edge dimensions, total span length, and total vertices, edges and mergers. We obtain bounds on these complexities as extensions of well-known dimension/length profile (DLP) bounds. Codes meeting these bounds minimize all the complexity measures simultaneously; conversely, a code attaining the bound for total span length, vertices, or edges, must likewise attain it for all the others. We define a notion of “uniform” optimality that embraces different domains of optimization, such as different permutations of a code or different codes with the same parameters, and we give examples of uniformly optimal codes and permutations. We also give some conditions that identify certain cases when no code or permutation can meet the bounds. In addition to DLP-based bounds, we derive new inequalities relating one complexity measure to another, which can be used in conjunction with known bounds on one measure to imply bounds on the others. As an application, we infer new bounds on maximum state and edge complexity and on total vertices and edges from bounds on span lengths
Maximum Distance Separable Codes and Arcs in Projective Spaces
Given any linear code over a finite field we show how can be
described in a transparent and geometrical way by using the associated
Bruen-Silverman code. Then, specializing to the case of MDS codes we use our
new approach to offer improvements to the main results currently available
concerning MDS extensions of linear MDS codes. We also sharply limit the
possibilities for constructing long non-linear MDS codes.Comment: 18 Pages; co-author added; some results updated; references adde
A Note on Cyclic Codes from APN Functions
Cyclic codes, as linear block error-correcting codes in coding theory, play a
vital role and have wide applications. Ding in \cite{D} constructed a number of
classes of cyclic codes from almost perfect nonlinear (APN) functions and
planar functions over finite fields and presented ten open problems on cyclic
codes from highly nonlinear functions. In this paper, we consider two open
problems involving the inverse APN functions and the Dobbertin
APN function . From the calculation of
linear spans and the minimal polynomials of two sequences generated by these
two classes of APN functions, the dimensions of the corresponding cyclic codes
are determined and lower bounds on the minimum weight of these cyclic codes are
presented. Actually, we present a framework for the minimal polynomial and
linear span of the sequence defined by ,
where is a primitive element in . These techniques can also be
applied into other open problems in \cite{D}
A Repair Framework for Scalar MDS Codes
Several works have developed vector-linear maximum-distance separable (MDS)
storage codes that min- imize the total communication cost required to repair a
single coded symbol after an erasure, referred to as repair bandwidth (BW).
Vector codes allow communicating fewer sub-symbols per node, instead of the
entire content. This allows non trivial savings in repair BW. In sharp
contrast, classic codes, like Reed- Solomon (RS), used in current storage
systems, are deemed to suffer from naive repair, i.e. downloading the entire
stored message to repair one failed node. This mainly happens because they are
scalar-linear. In this work, we present a simple framework that treats scalar
codes as vector-linear. In some cases, this allows significant savings in
repair BW. We show that vectorized scalar codes exhibit properties that
simplify the design of repair schemes. Our framework can be seen as a finite
field analogue of real interference alignment. Using our simplified framework,
we design a scheme that we call clique-repair which provably identifies the
best linear repair strategy for any scalar 2-parity MDS code, under some
conditions on the sub-field chosen for vectorization. We specify optimal repair
schemes for specific (5,3)- and (6,4)-Reed- Solomon (RS) codes. Further, we
present a repair strategy for the RS code currently deployed in the Facebook
Analytics Hadoop cluster that leads to 20% of repair BW savings over naive
repair which is the repair scheme currently used for this code.Comment: 10 Pages; accepted to IEEE JSAC -Distributed Storage 201
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