On the generalized Hamming weights of several classes of cycliccods

The generalized Hamming weights of a linear code are fundamental code parameters related to the minimal overlap structures of the subcodes. They were introduced by V.K. Wei (1991) and shown to characterize the performance of the linear code in certain cryptographical applications. Results are presented on the generalized Hamming weights of several classes of binary cyclic codes, including primitive double-error-correcting and triple-error-correcting BCH codes, certain reversible cyclic codes, and some extended binary Goppa codes. In particular, the second generalized Hamming weight of primitive double-error-correcting BCH codes is determined and upper and lower bounds are obtained for the generalized Hamming weights for the codes studied. These bounds are compared to results from other methods     

关于BCH码的广义Hamming重量上,下限

一个线性码的第ｒ广义Ｈａｍｍｉｎｇ重量是它任意ｒ维子码的最小支集大小。本文给出了一般（本原、狭义）ＢＣＨ码的广义Ｈａｍｍｉｎｇ重量下限和一类ＢＣＨ码的广义Ｈａｍｍｉｎｇ重量上限     

VI-2 class of Hamming weight of -aryq linear codes with dimension 5

The Hamming weight hierarchy of a linear [n,k;q] code c over GF(q)is the sequence(d₁,d₂,…,d_k),where d_r is the smallest support weight of an r-dimensional subcode of c.According to some new necessary conditions,the VI class Hamming weight hierarchies of q -ary linear codes of dimension 5 can be divided into six subclasses. By using the finite projective geometry method, VI-2 subclass and determine were researched almost all weight hierarchies of the VI-2 subclass of weight hierarchies of q -ary linear codes with dimension 5.     

Weight hierarchies of extremal non-chain binary codes of dimension4

The weight hierarchy of a linear [n,k;q] code C over GF(q) is the sequence (d₁,d₂,···,d_k ) where d_r is the smallest support of an r-dimensional subcode of C. An [n,k;q] code is extremal nonchain if, for any r and s, where 1⩽rS(D)=d_r, and w_S (E)=d_s. The possible weight hierarchies of such binary codes of dimension 4 are determined     

The normalized second moment of the binary lattice determined by aconvolutional code

Calculates the per-dimension mean squared error μ(S) of the two-state convolutional code C with generator matrix [1,1+D], for the symmetric binary source S=(0,1), and for the uniform source S={0,1}. When S=(0,1), the quantity μ(S) is the second moment of the coset weight distribution, which gives the expected Hamming distance of a random binary sequence from the code. When S={0,1}, the quantity μ(S) is the second moment of the Voronoi region of the module 2 binary lattice determined by C. The key observation is that a convolutional code with 2^υ states gives 2^υ approximations to a given source sequence, and these approximations do not differ very much. It is possible to calculate the steady state distribution for the differences in these path metrics, and hence, the second moment. The authors only give details for the convolutional code [1,1+D], but the method applies to arbitrary codes. They also define the covering radius of a convolutional code, and calculate this quantity for the code [1,1+D]     

VI-2类5维q元线性码的汉明重量谱的确定

上 线性码c的汉明重量谱为序列 ,其中,dr是c的r维子码的最小支撑重量。第VI类5维q元线性码的汉明重量谱,按照新的必要条件可以分成6个子类。运用有限射影几何方法研究VI-2类的5维q元线性码的汉明重量谱,确定VI-2类5维q元线性码的几乎所有汉明重量谱。     

Determination of the Local Weight Distribution of Binary Linear Block Codes

Some methods to determine the local weight distribution of binary linear codes are presented. Two approaches are studied: A computational approach and a theoretical approach. For the computational approach, an algorithm for computing the local weight distribution of codes using the automorphism group of the codes is devised. In this algorithm, a code is considered the set of cosets of a subcode, and the set of cosets is partitioned into equivalence classes. Thus, only the weight distributions of zero neighbors for each representative coset of equivalence classes are computed. For the theoretical approach, relations between the local weight distribution of a code, its extended code, and its even weight subcode are studied. As a result, the local weight distributions of some of the extended primitive Bose-Chaudhuri-Hocquenghen (BCH) codes, Reed-Muller codes, primitive BCH codes, punctured Reed-Muller codes, and even weight subcodes of primitive BCH codes and punctured Reed-Muller codes are determined     

An analysis of Chen's construction of minimum-distance five codes

In 1991, C.L. Chen used the inverted construction Y₁ on binary linear codes of minimum Hamming distance five to construct a new [47, 36, 5] code. We examine this construction in depth and show that no such codes are obtained unless the fields GF(8) or GF(32) are used. Using MAGMA, we prove that the binary [11, 4, 5] code and the binary [15, 7, 5] extension found by Chen are the only possible such codes using the field GF(8); indeed, the latter is a Bose-Chaudhuri-Hocquenghem (BCH) code. We prove also that, using the field GF(32), precisely three nonequivalent binary [47, 36, 5] codes arise along with one extension to a [63, 51, 5] code     

Generalized Hamming weights of linear codes

The generalized Hamming weight, d_r(C), of a binary linear code C is the size of the smallest support of any r-dimensional subcode of C. The parameter d_r(C) determines the code's performance on the wire-tap channel of Type II. Bounds on d_r(C), and in some cases exact expressions, are derived. In particular, a generalized Griesmer bound for d_r(C) is presented and examples are given of codes meeting this bound with equality     

Estimating the fraction of erasure patterns correctable by linear codes

The conditional probability (fraction) of the successful decoding of erasure patterns of high (greater than the code distance) weights is investigated for linear codes with the partially known or unknown weight spectra of code words. The estimated conditional probabilities and the methods used to calculate them refer to arbitrary binary linear codes and binary Hamming, Panchenko, and Bose–Chaudhuri–Hocquenghem (BCH) codes, including their extended and shortened forms. Error detection probabilities are estimated under erasure-correction conditions. The product-code decoding algorithms involving the correction of high weight erasures by means of component Hamming, Panchenko, and BCH codes are proposed, and the upper estimate of decoding failure probability is presented.     

On the second greedy weight for linear codes of dimension at least 4

The maximum of g/sub 2/ - d/sub 2/ for linear [n,k,d;q] codes C is studied. Here d/sub 2/ is the smallest size of the support of a two-dimensional subcode of C and g/sub 2/ is the smallest size of the support of a two-dimensional subcode of C which contains a codeword of weight d. For codes of dimension 4 or more, upper and lower bounds on the maximum of g/sub 2/-d/sub 2/ are given.     

广义Hamming重量上,下界的对偶定理

本文给出了一种广义Ｈａｍｍｉｎｇ重量上、下界的对偶定理。即若给定一个码的对偶码的广义Ｈａｍｍｉｎｇ重量上界（或者下界），可以给出该码的广义Ｈａｍｍｉｎｇ重量上界（或者下界）。Ｈ．Ｓｔｉｃｈ－ｎｏｔｈ（１９９４）曾给出了迹码（如ＢＣＨ码和Ｇｏｐｐａ码的对偶码）的广义Ｈａｍｍｉｎｇ重量一种上、下界，如果采用本文结果就可以给出迹码的对偶码的广义Ｈａｍｍｉｎｇ重量一种上、下界。因此，本文的结果是Ｈ．Ｓｔｉｃｈｎｏｔｈ的结果的有益补充     

On the weight hierarchy of Preparata codes over Z4

Hammons et al. (see ibid., vol.40, p.301-19, 1994) showed that, when properly defined, the binary nonlinear Preparata code can be considered as the Gray map of a linear code over Z₄, the so called Preparata code over Z₄. We consider the rth generalized Hamming weight d_r(m) of the Preparata code of length 2^m over Z₄. For any m⩾3, d_r(m) is exactly determined for r=0.5, 1, 1.5, 2, 2.5 and 3.0. For a composite m, we give an upper bound on d_r(m) using the lifting technique. For m=3, 4, 5, 6 and 8, the weight hierarchy is completely determined. In the case of m=7, the weight hierarchy is completely determined except for d₄(7)     

Some Remarks on BCH Bounds and Minimum Weights of Binary Primitive BCH Codes

It is shown that ifm neq 8, 12andm > 6, there are some binary primitive BCH codes (BCH codes in a narrow sense) of length2^{m} - 1whose minimum weight is greater than the BCH bound. This gives a negative answer to the question posed by Peterson [1] of whether or not the BCH bound is always the actual minimum weight of a binary primitive BCH code. It is also shown that for any evenm geq 6, there are some binary cyclic codes of length2^{m} - 1that have more information digits than the primitive BCH codes of length2^{m} - 1with the same minimum weight.     

Frequency-hopping code sequence designs having large linear span

In frequency-hopping spread-spectrum multiple-access communication systems, it is desirable to use sets of hopping patterns that, in addition to having good Hamming correlation properties and large period, are also derived from sequences having large linear span. Here, two such frequency hopping code sequence designs that are based on generalized bent functions and generalized bent sequences are presented. The Hamming correlation properties of the designs are optimal in the first case and close to optimal in the second. In terms of the alphabet size p (required to be prime in both cases), the period and family size of the two designs are given by (p², p) and (p ⁿ, p^n/2+1) (n an even integer), respectively. The finite field sequences underlying the patterns in the first design have linear span exceeding p, whereas still larger linear spans (when compared to the sequence period) can be obtained using the second design method     

关于几类线性分组码网格图复杂度的研究

本文研究了几类线性分组码C[n,k,d]的网格图复杂度s（C）。给出并证明了码长为奇数的两类线性分组码的网格图复杂度。同时得出了有关可纠t个错的本原BCH码[2^m-1,2^m-1-mt]及其扩展本在BCH码的网格图复杂度的若干结论。从而避免了必须先寻找码的直和结构才可得到码的网格图复杂度的较好上界。     

Bounds on the minimum support weights

The minimum support weight, d_r(C), of a linear code C over GF(q) is the minimal size of the support of an r-dimensional subcode of C. A number of bounds on d_r(C) are derived, generalizing the Plotkin bound and the Griesmer bound, as well as giving two new existential bounds. As the main result, it is shown that there exist codes of any given rate R whose ratio d_r/d₁ is lower bounded by a number ranging from (q^r-1)/(q^r -q^r-1) to r, depending on R     

Further results on generalized Hamming weights for Goethals andPreparata codes over Z4

This article contains results on the generalized Hamming weights (GHW) for the Goethals and Preparata codes over Z₄. We give an upper bound on the rth generalized Hamming weights d_r(m,j) for the Goethals code G_m(j) of length 2^m over Z ₄, when m is odd. We also determine d_3.5(m,j) exactly. The upper bound is shown to be tight up to r=3.5. Furthermore, we determine the rth generalized Hamming weight d_r(m) for the Preparata code of length 2^m over Z₄ when r=3.5 and r=4     

Design and analysis of codes with distance 4 and 6 minimizing the probability of decoder error

The problem of minimization of the decoder error probability is considered for shortened codes of dimension 2 ^m with distance 4 and 6. We prove that shortened Panchenko codes with distance 4 achieve the minimal probability of decoder error under special form of shortening. This shows that Hamming codes are not the best. In the paper, the rules for shortening Panchenko codes are defined and a combinatorial method to minimize the number of words of weight 4 and 5 is developed. There are obtained exact lower bounds on the probability of decoder error and the full solution of the problem of minimization of the decoder error probability for [39,32,4] and [72,64,4] codes. For shortened BCH codes with distance 6, upper and lower bounds on the number of minimal weight codewords are derived. There are constructed [45,32,6] and [79,64,6] BCH codes with the number of weight 6 codewords close to the lower bound and the decoder error probabilities are calculated for these codes. The results are intended for use in memory devices.     

On the minimum distance of cyclic codes

The main result is a new lower bound for the minimum distance of cyclic codes that includes earlier bounds (i.e., BCH bound, HT bound, Roos bound). This bound is related to a second method for bounding the minimum distance of a cyclic code, which we call shifting. This method can be even stronger than the first one. For all binary cyclic codes of length< 63(with two exceptions), we show that our methods yield the true minimum distance. The two exceptions at the end of our list are a code and its even-weight subcode. We treat several examples of cyclic codes of lengthgeq 63.