Two classes of linear codes and their generalized Hamming weights
Gaopeng Jian

TL;DR
This paper studies the generalized Hamming weights of two specific classes of linear codes, providing a complete determination using a number-theoretic approach, which advances understanding of their structural properties.
Contribution
It introduces a novel method employing number theory to fully determine the GHWs of these linear codes, filling a gap in existing literature.
Findings
Complete determination of GHWs for the two code classes
Application of number-theoretic techniques to code analysis
Enhanced understanding of code structure and parameters
Abstract
The generalized Hamming weights (GHWs) are fundamental parameters of linear codes. In this paper, we investigate the generalized Hamming weights of two classes of linear codes constructed from defining sets and determine them completely employing a number-theoretic approach.
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Taxonomy
TopicsCoding theory and cryptography · graph theory and CDMA systems · Error Correcting Code Techniques
Two classes of linear codes and their generalized Hamming weights
Gaopeng Jian
Zhouchen lin
Rongquan Feng
Key Laboratory of Machine Perception(MOE), School of EECS, Peking University, Beijing 100871, P.R.China
LMAM, School of Mathematical Sciences, Peking University, Beijing 100871, P.R.China
Abstract
The generalized Hamming weights (GHWs) are fundamental parameters of linear codes. In this paper, we investigate the generalized Hamming weights of two classes of linear codes constructed from defining sets and determine them completely employing a number-theoretic approach.
keywords:
Linear codes , Generalized Hamming weights , Exponential sums
1 Introduction
Let be the finite field with elements, where is an odd prime. An linear code over is a -dimensional subspace of the linear space . For any linear subcode , the support of is defined to be
[TABLE]
For , the -th generalized Hamming weight (GHW) of is given by
[TABLE]
where denotes the cardinality of . By definition, is just the minimum distance of . The set is called the weight hierarchy of .
The concept of GHWs was first introduced in [10, 14], and rediscovered by Wei [24] to fully characterize the performance of linear codes when used in a wire-tap channel of type II or as a t-resilient function. Indeed, the GHWs provide detailed structural information of linear codes, which can also be used to compute the state complexity of trellis diagrams for linear block codes [7], to determine the erasure list-decodability of linear codes [8] and so on.
In general, the determination of weight hierarchy is very difficult and there are only a few classes of linear codes whose weight hierarchies are known (see Section 4). In this paper, we construct two classes of linear codes and determine their weight hierarchies using exponential sums. In some cases they are optimal with respect to known bounds.
The rest of this paper is organized as follows. In Section 2, we review basic concepts and results on exponential sums together with previously known results on GHWs. In Section 3, we investigate the generalized Hamming weights of two classes of linear codes. In Section 4, we conclude this paper.
2 Preliminaries
2.1 Characters, cyclotomic classes and exponential sums over finite fields
We introduce several basic results on characters, cyclotomic classes and exponential sums used in this paper. For more details, please see Chapter 5 of the book [18].
Let be the finite field with elements, where is a power of a prime . Define the canonical additive character of as
[TABLE]
where is the primitive -th root of unity and is the trace function from to . The orthogonal property of additive characters is given by
[TABLE]
For and a positive integer such that , we define
[TABLE]
where denotes the cyclic subgroup of generated by . The cosets are called the cyclotomic classes of order in .
The Gaussian periods of order over are defined by
[TABLE]
Lemma 1**.**
Suppose that and . The Gaussian periods are given by
[TABLE]
and
[TABLE]
Let be an integer and , where is the least positive integer satisfying and . The values of the following exponential sum
[TABLE]
were determined in terms of Gauss periods in [15]. We summarize the results in the following lemma.
Lemma 2**.**
Let for some , where .
If b=0, then
[TABLE] 2. 2.
If , , then
[TABLE]
if , and are odd and
[TABLE]
otherwise.
2.2 Bounds and formulas of GHWs
Here we present three bounds on GHWs of linear codes. The reader may refer to the literature [23] for them.
Lemma 3**.**
Let be an linear code over . For ,
(1) Singleton type bound:
[TABLE]
* is called an -MDS code if .*
(2) Plotkin-like bound:
[TABLE]
(3) Griesmer-like bound:
[TABLE]
We recall a generic construction of linear codes proposed by Ding et al. [4]. Let , define a -ary linear code of length by
[TABLE]
The set is called the defining set of . Recently, many good linear codes were constructed by chosing appropriate defining sets [22, 28, 11, 5, 6, 26].
To calculate GHWs of the code , we present two formulas which are essentially proved in [27] (see also [12, 16]). For convenience we denote by the set of -dimensional subspaces of for any -linear space and for any .
Lemma 4**.**
Suppose that and . For ,
[TABLE]
Lemma 5**.**
Suppose that and . For ,
[TABLE]
where
[TABLE]
3 Main results and proofs
From now on we fix the following notations.
, is an odd prime, is a positive integer with .
- 2.
is a primitive element of .
- 3.
or .
- 4.
, we only consider the case that is an odd integer if .
- 5.
is the primitive -th root of unity.
- 6.
is the canonical additive character of .
- 7.
is the trace function from to .
- 8.
The defining set of the code is
[TABLE]
- 9.
.
Let be a mapping from to defined by
[TABLE]
for each . Obviously, is -linear and the image of is . If , we shall see that is injective and thus induces a 1-1 correspondence between and for . If , however is not injective and the kernel of is . It’s easy to see that is a -dimensional subspace of and . Then induces a 1-1 correspondence between and for .
By the orthogonal property of additive characters we can determine the length and dimension of .
Theorem 1**.**
Let and , then
[TABLE]
and
[TABLE]
Proof.
By definition,
[TABLE]
and for , the Hamming weight of is
[TABLE]
If ,
[TABLE]
If ,
[TABLE]
and is the zero vector if . So . 2. 2.
If , by Lemma 2,
[TABLE]
where for . Let , which is a primitive element of , then
[TABLE]
Since , . Let I=\{f:\text{f is an even number with }0\leq f\leq p-2\}. Note that is a primitive element of , then
[TABLE]
By Lemma 1 and formula (1), (2)
[TABLE]
So if , the defining set is empty and . If , let , . We have noting that is a primitive element of and . By Lemma 1, 2 and formula (2)
[TABLE]
which implies that .
∎
Now we determine GHWs of the code .
Theorem 2**.**
If , then
[TABLE]
Proof.
Indeed we can not use Lemma 4 directly, but by the same principle we have
[TABLE]
for . ∎
Remark 1**.**
By formula (3) it’s easy to check that is -MDS and meets the Plotkin-like bound and the Griesmer-like bound for all .
Example 1**.**
Let and , then is a linear code over with and is 2-MDS. meets the Plotkin-like bound and the Griesmer-like bound for all .
Example 2**.**
Let and , then is a linear code over with , , , and . is 5-MDS. meets the Plotkin-like bound and the Griesmer-like bound for all .
Theorem 3**.**
If and , then
[TABLE]
Proof.
With the symbols defined in Lemma 5. For , let
[TABLE]
[TABLE]
Let and , then .
If , note that since is a primitive element of and . We can choose , where , and . By Lemma 5,
[TABLE]
If , note that for any , which implies that is contained in for any . We can choose and . By Lemma 4,
[TABLE]
∎
Remark 2**.**
By formula (4) it’s easy to check that is -MDS, meets the Griesmer-like bound for and meets the Plotkin-like bound.
Example 3**.**
Let and , then is a linear code over with and . is 2-MDS. meets the Plotkin-like bound.
Example 4**.**
Let and , then is a linear code over with , , , , and . is 6-MDS. meets the Griesmer-like bound for . meets the Plotkin-like bound.
4 Concluding remarks
The weight hierarchy of a code has been examined at least in the following cases:
Hamming codes 2. 2.
Golay codes 3. 3.
Product codes. 4. 4.
Codes from classical varieties: Reed–Muller codes, Algebraic geometric codes, codes from quadrics, Hermitian varieties, Grassmannians, Del Pezzo surfaces. 5. 5.
Binary Kasami codes. 6. 6.
Cyclic and trace codes: BCH, Melas. 7. 7.
Codes parameterized by the edges of simple graphs.
A survey up to known results until 1995 was done in [23]. Recent results can be found in [27, 1, 25, 21, 9, 17, 12, 13, 2, 20, 3, 16, 19].
Acknowledgments
G.Jian and Z.Lin are supported by National Natural Science Foundation (NSF) of China (grant no.61625301). R.Feng is supported by the NSFC-Genertec Joint Fund For Basic Research (grant no.U1636104).
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- 2Beelen [2018] Beelen, P., 2018. A note on the generalized Hamming weights of Reed–Muller codes. Applicable Algebra in Engineering, Communication and Computing, 1–10.
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- 4Ding and Niederreiter [2007] Ding, C., Niederreiter, H., 2007. Cyclotomic linear codes of order 3. IEEE Transactions on Information Theory 53 (6), 2274–2277.
- 5Ding and Ding [2014] Ding, K., Ding, C., 2014. Binary linear codes with three weights. IEEE Communications Letters 18 (11), 1879–1882.
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