1. Introduction
With the rapid development of information technology and the popularity of the Internet, network communication has become an indispensable infrastructure in modern society. However, as the scale of the network expands and its structure becomes more complex, network coding and network communication face many challenges, such as increasingly prominent issues related to the reliability, effectiveness, and security of information transmission. To address these challenges, researchers continue to explore new coding technologies and methods to improve the performance of communication systems.
During the research process, it was discovered that monomial codes [
1], cyclic codes, LDPC codes, and particularly cyclic subspace codes play significant roles in network coding. Among these codes, cyclic subspace codes exhibit a series of superior characteristics. Owing to their unique cyclic subspace structure, cyclic subspace codes cleverly utilize cyclic shifts and linear algebra operations in the encoding and decoding processes, thereby greatly simplifying the operational procedures and achieving efficient encoding and decoding algorithms [
2,
3,
4]. Furthermore, with their special codeword structure design, cyclic subspace codes demonstrate excellent error detection and correction capabilities in complex communication environments with noise and interference. Notably, by meticulously constructing codewords with a larger minimum Hamming distance, cyclic subspace codes can maintain a low bit error rate in communication channels with high noise levels, ensuring the reliability of communication. However, there are still some deficiencies in cyclic subspace codes. Therefore, this paper is dedicated to constructing cyclic subspace codes with better performance using Sidon spaces.
Sidon spaces, as a key instrument in constructing such codes, optimize the encoding process by providing well-structured sets of subspaces [
5]. Together, they provide a solid theoretical foundation for efficient data transmission, distributed storage, and future communication technologies. Next, we will introduce some theoretical knowledge related to cyclic subspace codes and Sidon spaces.
Let q be a prime power and let be the finite field of q elements which is the field of scalars. The vector space of dimension n over is expressed as the extension field .
The projective space of order
n over
, denoted as
, is the family of all subspaces of the vector space
[
6]. To quantify the separation between arbitrary elements
U and
V in
, we introduce the subspace distance
given by the expression
where
denotes the dimension of a vector space over
. With this foundation, we can define an
code
in the projective space, which is a subset of
containing
M elements, with the distance between any two codewords ( subspaces) being at least
d [
6]. For any element
, the cyclic shift
of
U by an element
is the set
. Notably,
retains the same dimension as
U. The set of all such shifts, orb
, comprises
and its size is
, where
t divides
n. A full-length orbit code arises when orb
attains its maximum size of
. Such codes exhibit a minimum distance no greater than
, and optimality is achieved when this bound is met [
7]. The notation
signifies the collection of all
k-dimensional subspaces of
.
Given positive integers n and k, a k-dimensional subspace code is a non-empty subset of . Specifically, if forms a subspace code and includes the orbit of every , then is classified as a cyclic subspace code.
The concept of subspace codes was initially introduced in paper [
8], as documented in [
9,
10,
11]. Among them, cyclic subspace codes stand out due to their superior properties, enabling efficient encoding and decoding processes, as discussed in [
5]. The construction of cyclic subspace codes typically follows two distinct paths. The first approach leverages the roots of linearized polynomials, a method initially proposed by Ben-Sasson in [
12]. Utilizing the roots of these specialized polynomials, this technique has been successfully employed to construct cyclic subspace codes in
with a minimum distance of
, as detailed in [
12,
13,
14]. Alternatively, the second approach exploits Sidon spaces to construct cyclic subspace codes, a topic explored in [
15,
16,
17,
18]. Given the extensive research conducted by numerous prominent scholars on cyclic subspace codes, we will delve into some of the pioneering construction methods in the subsequent paragraphs, as in
Table 1.
(1) In [
19], Roth et al. constructed a great number of large cyclic subspace codes in
with a minimum distance of
by utilizing the Sidon space
, and subsequently obtained cyclic subspace codes of size
. Furthermore, they confirmed that constructing a Sidon space in
is equivalent to constructing a cyclic subspace code of size
in the same space.
(2) In [
20], Feng et al. constructed a great number of large cyclic subspace codes in
with a minimum distance of
by utilizing the Sidon spaces
and subsequently obtained cyclic subspace codes of size
.
(3) In [
21], Li et al. constructed a great number of large cyclic codes in
whose minimum distance was
through utilizing the Sidon space
Furthermore, they successfully proved that if there exist
m distinct Sidon spaces that satisfy some conditions, then the sum of these
m Sidon spaces once again forms a Sidon space.
(4) In [
16], Liu et al. constructed a great number of large cyclic codes in
with a minimum distance of
by utilizing the Sidon space
and subsequently obtained cyclic subspace codes with size
. Moreover, by making use of
they received additional cyclic subspace codes with size
. Finally, they received a new cyclic subspace code whose size was
.
Table 1.
The comparison of Sidon spaces and cyclic subspace codes.
Table 1.
The comparison of Sidon spaces and cyclic subspace codes.
Reference | Sidon Spaces | dim(C) | d(C) | Code Sizes |
---|
[18] |
| k | | |
[21] |
| | | |
[22] |
| | | |
[23] | | k | | |
[24] |
| k | |
|
[25] |
| k | | |
Theorem 3 |
| | | |
Theorem 4 |
| | | |
In this paper, we endeavor to construct new Sidon spaces by utilizing the roots of irreducible polynomials and primitive elements defined over finite fields. Furthermore, we introduce a new class of cyclic subspace codes, whose sizes are multiples of , and possess a minimum distance of , thereby contributing to the advancement of the field.
The structure of this paper is outlined as follows.
Section 1 presents the conceptual framework for constructing cyclic subspace codes.
Section 2 establishes the preliminary theoretical foundations essential for the subsequent constructions. In
Section 3, we construct Sidon spaces
and
that have new parameters and better encoding. Based on the Sidon spaces constructed in
Section 3, we present a cyclic subspace code of size
and
, along with its proof in
Section 4. Finally,
Section 5 concludes the paper by providing a comprehensive summary of our key findings and contributions, highlighting the significance and implications of our work within the broader research landscape.
3. Constructions of Sidon Spaces
In this section, we first review some basic definitions. Subsequently, with the help of these facts, we construct several Sidon spaces with dimension .
Given three positive integers k, , and , which satisfy the condition that ; and then given a prime power q and given a primitive element in ; and, in addition, being a root of an irreducible polynomial over whose degree is , and being a root of an irreducible polynomial over whose degree is , for any positive integer and with , we let . For any positive integer and with , we let , . Moreover, we let .
Theorem 1. We keep the notations above. Moreover, we let , where . We define . Hence, we can obtain that is a -dimensional Sidon space.
Proof. If
, then we should check
It is obvious that
is an independent linear set. By comparing the coefficients of the equations in
, we obtain
Next, with the help of , we will prove this theorem from the subsequent four cases.
Case: and .
From and in , we can have that , . Hence, the equation can be simplified to .
. .
By simplifying the equations above, we obtain . Then, we let . Hence, we obtain , as well as . Thus, we obtain .
. .
When , as well as , we have , and then we obtain .
Case: and .
Next, we will discuss this case from the following three aspects.
. The case that , , , and have only one or three zeroes is impossible.
. If , , , and have two zeroes, assuming that and , then we have . Hence, we have .
. If , , , and have four zeroes, as well as , we have .
Case: and .
Next, we will discuss this case from the following three aspects.
. The case that , , , and have only one or three zeroes is impossible.
. If , , , and have two zeroes, assuming that and , then we have . Hence, we have .
. If , , , and have four zeroes, as well as , we have .
Case: and .
If we have four zeroes, as well as , then we let . Hence, we have .
From Definition 1, we can obtain that is a -dimensional Sidon space.
This ends the proof. □
Corollary 1. Similarly, we can obtain that is a -dimensional Sidon space.
Proof. If
, then we should check
It is obvious that
is an independent linear set. By comparing the coefficients of the equations in
, we obtain
The remaining proofs are similar to Theorem 1, and we omit them here. □
Theorem 2. We keep the notations above. Moreover, we let . We define . Hence, we can obtain that is a -dimensional Sidon space.
Proof. When , the case is trivial and clearly holds. We only consider the case where below.
If
, then we should check
It is obvious that
is an independent linear set. By comparing the coefficients of the equations in
, we obtain
From the equations above, we can have that , and then we get .
From Definition 1, we can obtain that is a -dimensional Sidon space.
This ends the proof. □
4. Constructions of Cyclic Subspace Codes
In this section, we first review some basic definitions. Subsequently, with the help of these facts and the newly constructed Sidon spaces in
Section 3, we construct several cyclic subspace codes.
Theorem 3. We use the notations from Theorem 1. Moreover, we let , where , . We define . We let , and then the subspace code is a cyclic constant dimension subspace code whose size is and minimum distance is .
Proof. We know that each
is a Sidon space according to
Theorem 1 and every
is a cyclic subspace code of size
and minimum distance
by
Lemma 2. In order to verify that
has a minimum distance of
, we should prove that
. From
Lemma 3, we know that it is equivalent to verify
where
.
Firstly, we let
be four nonzero elements such that
.
. .
It is obvious that
is an independent linear set. By comparing the coefficients of the equations in
, we obtain
From and in , we can have that , . Hence, the equations and can be simplified to and .
. .
From the equations above, we obtain and . Then, we can obtain , which is contradictory to the fact that . Hence, we will not discuss it.
. .
When , as well as , we have , and then we obtain .
. .
It is obvious that
is an independent linear set. By comparing the coefficients of the equations in
, we obtain
From the equations above, we have , and then we obtain .
To conclude, we have successfully verified that
has a minimum distance of
by
Lemma 2. In particular, we have also verified that the
elements of
are different, so
This ends the proof. □
Corollary 2. Similarly, we define to be as in Corollary 1. We let , and then the subspace code is a cyclic constant dimension subspace code whose size is and minimum distance is .
Proof. We know that each
is a Sidon space according to
Corollary 1 and every
is a cyclic subspace code of size
and minimum distance
by
Lemma 2. In order to verify that
has a minimum distance of
, we should prove that
. From
Lemma 3, we know that it is equivalent to verify
where
. Let
be four nonzero elements such that
.
The remaining proofs are similar to Theorem 3, and we omit them here. □
Theorem 4. We use the notations from Theorem 2. Moreover, we let . We define the Sidon space . We let , and then the subspace code ; then, the subspace code is a cyclic constant dimension subspace code whose size is and minimum distance is .
Proof. We know that each
is a Sidon space according to
Theorem 2 and every
is a cyclic subspace code of size
and minimum distance
by
Lemma 2. In order to verify that
has a minimum distance of
, we should prove that
. From
Lemma 3, we know that it is equivalent to verify
where
. Firstly, we let
be four nonzero elements such that
.
It is obvious that
is an independent linear set. By comparing the coefficients of the equations in
, we obtain
From the equations above, we have , and then we obtain .
To conclude, we have successfully verified that
has a minimum distance of
by
Lemma 2. In particular, we have also verified that the
elements of
are different, so
This end the proof. □
Theorem 5. We use the notations from Theorems 1 and 2. Then, we let and be the codes constructed in Theorems 3 and 4. Let , where , . The subspace code is a cyclic constant dimension subspace code whose size is and minimum distance is .
Proof. We know that each of
is a Sidon space according to
Theorems 3 and
4. In order to verify that
has a minimum distance of
, we should prove that
. From
Lemma 3, we know that is equivalent to verify
where
. Firstly, we let
be four nonzero elements such that
.
. .
It is obvious that
is an independent linear set. By comparing the coefficients of the equations in
, we obtain
From and in , we can have that , . Hence, the equations and can be simplified to and .
. .
From the equations above, we obtain and . Then, we can obtain , which is contradictory to the fact that . Hence, we will not discuss it.
. .
When , we have , and then we obtain .
. .
It is obvious that
is an independent linear set. By comparing the coefficients of the equations in
, we obtain
From the equations above, we have , and then we obtain .
To conclude, we have successfully verified that
has a minimum distance of
by
Lemma 2. Thus,
This ends the proof. □
Corollary 3. Similarly, we let and be the codes constructed in Theorem 4 and Corollary 2. The subspace code is a cyclic constant dimension subspace code whose size is and minimum distance is .
Proof. We know that each of
is a Sidon space according to
Corollary 1 and
Theorem 2. In order to verify that
has a minimum distance of
, we should prove that
. From
Lemma 3, we know that it is equivalent to verify
where
. Let
be four nonzero elements such that
.
The remaining proofs are similar to Theorem 5, and we omit them here. □
Example 1. We let . Then, . Thus, . Hence, the cyclic subspace code constructed in Theorem 5 has a size .