On deep holes of generalized projective Reed-Solomon codes
Xiaofan Xu, Shaofang Hong, Yongchao Xu

TL;DR
This paper characterizes deep holes in generalized projective Reed-Solomon codes over finite fields, linking their existence to specific sum conditions on subsets of the evaluation set, and extends understanding of decoding limits.
Contribution
It provides a complete characterization of deep holes in GPRS codes using sum conditions, and introduces new criteria involving polynomial degrees and subset sums for identifying deep holes.
Findings
Deep holes correspond to nonzero subset sums of elements in the evaluation set.
Characterization of deep holes for polynomials of degree k.
Special conditions for deep holes when the characteristic divides k.
Abstract
Determining deep holes is an important topic in decoding Reed-Solomon codes. Let be an integer and be arbitrarily given distinct elements of the finite field of elements with the odd prime number as its characteristic. Let and be an integer such that . In this paper, we study the deep holes of generalized projective Reed-Solomon code of length and dimension over . For any , we let if and be the coefficient of of . By using D\"ur's theorem on the relation between the covering radius and minimum distance of , we show that if with , then the received codeword $(u(D),…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsCoding theory and cryptography · graph theory and CDMA systems · Finite Group Theory Research
On deep holes of generalized projective Reed-Solomon codes
Xiaofan Xu
Mathematical College, Sichuan University, Chengdu 610064, P.R. China
,
Shaofang Hong
Mathematical College, Sichuan University, Chengdu 610064, P.R. China
[email protected], [email protected], [email protected]
and
Yongchao Xu
Mathematical College, Sichuan University, Chengdu 610064, P.R. China
Abstract.
Determining deep holes is an important topic in decoding Reed-Solomon codes. Cheng and Murray, Li and Wan, Wu and Hong investigated the error distance of generalized Reed-Solomon codes. Recently, Zhang and Wan explored the deep holes of projective Reed-Solomon codes. Let be an integer and be arbitrarily given distinct elements of the finite field of elements with the odd prime number as its characteristic. Let and be an integer such that . In this paper, we study the deep holes of generalized projective Reed-Solomon code of length and dimension over . For any , we let if and be the coefficient of of . By using Dür’s theorem on the relation between the covering radius and minimum distance of , we show that if with , then the received codeword is a deep hole of if and only if the sum is nonzero for any subset with . We show also that if is an integer with and with , and being a polynomial of degree at most , then is a deep hole of if and only if the sum is nonzero for any subset with , where is the identity of the group . This implies that is a deep hole of if . We also deduce that is a deep hole of the primitive projective Reed-Solomon code if with and . But is not a deep hole of if .
Key words and phrases:
generalized projective Reed-Solomon code, MDS code, deep hole, Lagrange interpolation polynomial, generator matrix
2000 Mathematics Subject Classification:
Primary 11B25, 11N13, 11A05
S. Hong is the corresponding author and was supported partially by National Science Foundation of China Grant # 11371260.
1. Introduction and the statements of the main results
Let be the finite field of elements with as its characteristic. Let and be positive integers such that . Let be a subset of , which is called the evaluation set. The generalized Reed-Solomon code of length and dimension over is defined by:
[TABLE]
Moreover, the generalized projective Reed-Solomon code of length and dimension over is defined as follows:
[TABLE]
where is the coefficient of of . If , then it is called primitive projective Reed-Solomon code, namely,
[TABLE]
where is a primitive element of . If , then it is called the extended projective Reed Solomon code. For , , the Hamming distance is defined by
[TABLE]
For any linear code , the minimum distance is defined by
[TABLE]
where denotes the Hamming distance of two words. A linear code is called maximum distance separable (MDS) code if . The error distance to code of a received word is defined by
[TABLE]
Clearly, if and only if . The covering radius to code of a received word is defined by
[TABLE]
The most important algorithmic problem in coding theory is the maximum likelihood decoding (MLD): Given a received word , find a word such that , then we decode to [7]. Therefore, it is very crucial to decide for the word . Guruswami and Sudan [3] provided a polynomial time list decoding algorithm for the decoding of when . When the error distance increases, Guruswami and Vardy [4] showed that that maximum-likelihood decoding is NP-hard for the family of Reed-Solomon codes. We also notice that Dür [2] studied the Cauchy codes. In particular, Dür [2] got the relation between the covering radius and minimum distance of . When decoding the generalized projective Reed-Solomon code ,for a received word , we define the Lagrange interpolation polynomial of by
[TABLE]
i.e., is the unique polynomial of degree such that for and . It is clear that if and only if if and only if . Equivalently, if and only if if and only if . Evidently, we have the following simple bounds of which are due to Li and Wan.
Theorem 1.1. [6] Let be a received word such that . Then
[TABLE]
Let . If , then the received word is called a deep hole of . In 2007, Cheng and Murray [1] conjectured that a word is a deep hole of if and only if , where is the Lagrange interpolation polynomial of the received word and , a polynomial of degree at most . In 2012, Wu and Hong [9] disproved this conjecture by giving a new class of deep holes for Reed-Solomon codes . In fact, if and , then they showed that the received word is a deep hole if its Lagrange interpolation polynomial is . In [5], Hong and Wu proved that the received word is a deep hole of the generalized Reed-Solomon codes if its Lagrange interpolation polynomial is , where and a polynomial of degree at most
Throughout this paper, we always let be a positive integer and be any fixed distinct elements of . Let
[TABLE]
We write
[TABLE]
and for any , we let
[TABLE]
and use to denote the coefficient of of . Then we can rewrite the generalized projective Reed-Solomon code with evaluation set as
[TABLE]
Let . If , then is also called a deep hole of generalized projective Reed-Solomon code . In 2016, Zhang and Wan [10] studied the deep holes of projective Reed-Solomon code . In fact, under the assumption that the only deep holes of are those received codewords whose Lagrange interpolation polynomials are of degree , they proved the following results by solving a subset sum problem.
Theorem 1.2. [10] *Let be an odd prime power. Assume that or . Then the received codeword with is a deep hole of .
Theorem 1.3. [10] *Let and . If there are positive constants and such that , then is not a deep hole of .
In this paper, our main goal is to investigate the deep holes of the generalized projective Reed-Solomon codes . Actually, we will present characterizations for the received codewords of degrees and to be deep holes of generalized projective Reed-Solomon code . The main results of this paper can be stated as follows.
Theorem 1.4. *Let be a prime power and and be positive integers such that and . Let with . Then the received codeword is a deep hole of the generalized projective Reed-Solomon code if and only if the sum is nonzero for any subset with .
Theorem 1.5. Let be a prime power and and be positive integers such that and . Let be an integer with and let with , and being a polynomial of degree at most . Then the received codeword is a deep hole of the generalized projective Reed-Solomon code if and only if the sum is nonzero for any subset with , where is the identity of the multiplicative group .
*Further, if , then the received codeword is a deep hole of .
From Theorems 1.4 and 1.5, we can derive the following results on the deep holes of the primitive projective Reed-Solomon codes. Note that the proof of Theorem 1.6 relies also on a result on the zero subsets sum of the group (see Lemma 2.8 below).
Theorem 1.6. *Let be an odd prime power such that and . If with and being a polynomial of degree at most , then the received codeword is not a deep hole of the primitive projective Reed-Solomon code .
Theorem 1.7. *Let and . If with and being a polynomial of degree at most , then the received codeword is a deep hole of the primitive projective Reed-Solomon code .
In the proofs of Theorems 1.4 and 1.5, the basic tools are the MDS code and Vandemonde determinant. But we would also like to point out that a key ingredient in the proofs is Dür’s theorem on the relation between the covering radius and minimum distance of the generalized projective Reed-Solomon code (see Lemma 2.6 below). Another important ingredient is a new result on the zero-sum problem in the finite field that we will prove in the next section.
This paper is organized as follows. First of all, in Section 2, we recall and prove several preliminary lemmas that are needed in the proof of Theorems 1.4 and 1.5. Consequently, in Section 3, we use the lemmas presented in Section 2 to give the proofs of Theorems 1.4 and 1.6. Finally, by using the results given in Section 2, we supply in Section 4 the proofs of Theorems 1.5 and 1.7.
2. Preliminary lemmas
In this section, our main aim is to prove several lemmas that are needed in the proof of Theorems 1.4 and 1.5. We begin with the following result on MDS codes.
Lemma 2.1. *Let be a MDS code and be a given codeword. Then the received codeword is a deep hole of if and only if the received codeword is a deep hole of .
Proof. First of all, let be a received codeword. Then by the definition of deep hole, one knows that is a deep hole of if and only if with being the covering radius of , if and only if
[TABLE]
Likewise, one has that the received codeword is a deep hole of if and only if
[TABLE]
Since
[TABLE]
it follows that
[TABLE]
But for any codeword . Hence (2.3) tells us that
[TABLE]
Now from (2.1), (2.2) and (2.4), one can deduce that is a deep hole of if and only if is a deep hole of as one desires. So Lemma 2.1 is proved.
Remark 2.1. We should point out that if the codeword is not in , then Lemma 2.1 is not true.
In what follows, we let
[TABLE]
We have the following result.
Lemma 2.2. Let and let and be two codewords with and being the Lagrange polynomials of and . If , where and is a polynomial of degree at most , then
[TABLE]
*Further, is a deep hole of if and only if is a deep hole of
Proof. Since , we have and . By the definition of Hamming distance, we know that for any code over , if and are codewords of , then
[TABLE]
hold for any codeword of and any . Then from the definition of error distance and noticing that , we can deduce immediately that
[TABLE]
as required. The proof of Lemma 2.2 is complete.
For a linear code with and being the length and dimension of , respectively, we define the generator matrix, denoted by , to be the matrix of the form , where is a basis of as a vector space. Since , the following matrix
[TABLE]
forms a generator matrix of . For the purpose of this paper, we will choose the above matrix as the generator matrix of .
Lemma 2.3. [8] *Let be an linear code and be the generator matrix of . Then is a MDS code if and only if any distinct columns of are linear independent over finite field .
Throughout this paper, for any nonempty set , we define the Vandermonde determinant, denoted by , as follows:
[TABLE]
We have the following well-known result.
Lemma 2.4. [8] One has
[TABLE]
In the following, we show that the generalized projective Reed-Solomon code is a MDS code.
Lemma 2.5. *Let . Then is a MDS code over finite field .
Proof. Let be the generator matrix of given in (2.5). Write . Let be arbitrary distinct integers such that We claim that which will be proved in what follows.
If , then it follows that
[TABLE]
The claim is true in this case.
If , then by expanding the determinant according to the last column, we arrive at
[TABLE]
The claim is proved in this case.
Now by the claim, we can derive that any columns of the generator matrix is linear independent. Then is a MDS code by Lemma 2.3.
This concludes the proof of Lemma 2.5.
The following result about the relation between the covering radius and minimum distance of will play a key role in this paper which is due to Dür [2].
Lemma 2.6. [2] Let be a proper subset of . Then
[TABLE]
The following result is well known.
Lemma 2.7. [11] *Let be a generator matrix of a MDS code over the finite field . If the covering radius , then a received codeword is a deep hole of if and only if the matrix \left(\begin{array}[]{c}{G}\\ {u}\end{array}\right) can be served as the generator matrix of another MDS code.
In what follows, we show a result on the zero-sum problem in the finite field of odd characteristic.
Lemma 2.8. *Let with being an odd prime number and be an integer with . Then there exist a subset with such that .
Proof. Since is an odd prime number, it follows that for any , one has and since . But since . Now one can pick . Then since . Continuing in this way, we finally arrive at
[TABLE]
We consider the following cases.
Case 1. . In this case, we let . Then and we have
[TABLE]
as desired. Lemma 2.8 holds if .
Case 2. . Then and so since . We claim that there are three distinct elements such that , which will be proved by dividing into the following three subcases.
Case 2.1. . We pick a . Then , and . The latter implies that . Since and , we deduce that . Thus . So we can choose a . But . Hence . It implies that , namely, . Furthermore, we have that is not equal to anyone of the four elements and . That is, . Hence . Therefore there are three distinct elements and in such that their sum equals zero. The claim holds in this case.
Case 2.2. . Take a . Then and none of and equals zero. It follows that the four elements are pairwise distinct. Since , one must have . Thus . So we can choose . Then and . The latter one tells us that . Obviously, since . Hence .
Furthermore, we can deduce that is not equal to any of and . This infers that since . Therefore we can find three distinct elements and in such that their sum equals zero. The claim holds in this case. The claim is proved in this case.
Case 2.3. . Then for any integer with , where stands for the identity of the group . Since and , we have and . So there are three different elements in such that their sum is equal to zero as one desires. The claim is true in this case.
Now by the claim, we know that there are three integers and such that and .
If , then letting gives us the desired result.
If , then is nonempty. By (2.6), we obtain that
[TABLE]
Since , is even. Evidently, the sum of the first elements on the right hand side of (2.7) is equal to zero because for all integers . Then the first elements on the right hand side of (2.7) together with the three elements gives us the desired result. Thus Lemma 2.8 is true if .
This completes the proof of Lemma 2.8.
For any positive integer , we define its -adic valuation, denoted by , to be the largest exponent such that divides . In the conclusion of this section, We provide the following characterization on the divisibility of certain binomial coefficients by the prime number .
Lemma 2.9. Let be a power of the odd prime and let be an integer with . Then v_{p}\big{(}\binom{q-2}{t-1}\big{)}=v_{p}(t). Consequently, the binomial coefficient is divisible by if and only if is a multiple of .
Proof. Clearly, one has
[TABLE]
Therefore
[TABLE]
Since is a power of , it follows that for any positive integer with , one has , and so
[TABLE]
Then from (2.8) and (2.9) one derives that
[TABLE]
as required. It then follows that if and only if . So Lemma 2.9 is proved.
3. Proofs of Theorems 1.4 and 1.6
In this section, we use the lemmas presented in the previous to give the proofs of Theorems 1.4 and 1.6. At first, we show Theorem 1.4.
Proof of Theorem 1.4. Since , one may let with and being a polynomial of degree at most . Then . By Lemma 2.2, we have that is a deep hole of the generalized projective Reed-Solomon code if and only if is a deep hole of . But
[TABLE]
where and
[TABLE]
Then one has
[TABLE]
Since , by the definition of we have . Then it follows from Lemma 2.1 that is a deep hole of if and only if is a deep hole of . Then we can deduce that is a deep hole of if and only if is a deep hole of .
We denote . Let be the generator matrix of as given in (2.5). Then we have
[TABLE]
Now we pick distinct integers with .
Case 1. . Then one has
[TABLE]
Case 2. . We can compute and get that
[TABLE]
Now we introduce an auxiliary polynomial as follows:
[TABLE]
Then Lemma 2.4 tells us that
[TABLE]
It infers that
[TABLE]
But
[TABLE]
Finally, (3.1) together with (3.2) and (3.3) gives us that
[TABLE]
By Lemma 2.5, we know that is a MDS code which implies that
[TABLE]
Then by Lemma 2.6, one can deduce that
[TABLE]
It then follows immediately from Lemma 2.7 that is a deep hole of the generalized projective Reed-Solomon code if and only if the matrix \left(\begin{array}[]{c}G\\ {\bar{w}_{k}}\end{array}\right) can be served as the generator matrix of a MDS code, if and only if any columns of \left(\begin{array}[]{c}G\\ {\bar{w}_{k}}\end{array}\right) are linear independent, if and only if for any , one has
[TABLE]
By the discussion in Cases 1 and 2, (3.4) tells us that (3.6) holds if and only if for any , one has . Hence we can derive that is a deep hole of the generalized projective Reed-Solomon code if and only if the sum is nonzero for any subset with as desired.
Finally, we can conclude that is a deep hole of the generalized projective Reed-Solomon code if and only if the sum is nonzero for any subset with .
This finishes the proof of Theorem 1.4.
We can now use Theorem 1.4 to show Theorem 1.6.
Proof of Theorem 1.6. Let and . Then . By Lemma 2.8, there exist a subset with such that . It then follows from Theorem 1.4 that the received word = is not a deep hole of the primitive projective Reed-Solomon code . Therefore Theorem 1.6 is proved.
4. Proofs of Theorems 1.5 and 1.7
In this section, we give the proof of Theorems 1.5 and 1.7. We begin with the proof of Theorem 1.5.
Proof of Theorem 1.5. First of all, we note that is an integer with . We introduce a polynomial as follows:
[TABLE]
and define a codeword associated to by
[TABLE]
Then which implies that
[TABLE]
It follows from (4.1) that
[TABLE]
But
[TABLE]
and
[TABLE]
Hence
[TABLE]
It follows from Lemmas 2.1 and 2.2 that the received word is a deep hole of the generalized projective Reed-Solomon code if and only if is a deep hole of .
Let be the generator matrix of as given in (2.5). Since for all integers with , we have . It then follows that
[TABLE]
On the other hand, from Lemma 2.7 we can deduce that is a deep hole of the generalized projective Reed-Solomon code , if and only if \left(\begin{array}[]{c}G\\ {\bar{f}_{j}}\end{array}\right) generates a MDS code, by Lemma 2.3, if and only if any columns of \left(\begin{array}[]{c}G\\ {\bar{f}_{j}}\end{array}\right) are linear independent, if and only if for all integers with , one has
[TABLE]
In what follows, we choose arbitrarily integers such that . Consider the following two cases.
Case 1. . Then and by (4.2), one has
[TABLE]
Thus one can deduce that
[TABLE]
[TABLE]
since are pairwise distinct.
Case 2. . Then . From (4.2) and Lemma 2.4, we can deduce that
[TABLE]
Now from Cases 1 and 2, we can deduce by (4.4) that (4.3) holds for all integers with if and only if for all integers with , one has
[TABLE]
which is equivalent to
[TABLE]
Since , the binomial theorem gives us that
[TABLE]
Then one derives that (4.5) holds for all integers with if and only if the following is true:
[TABLE]
or equivalently,
[TABLE]
since is odd. In other words, is a deep hole of the generalized projective Reed-Solomon code if and only if the sum
[TABLE]
is nonzero for any subset with . Hence the desired result follows immediately. The first part is proved.
Now we show the second part. Let . Then by Lemma 2.9, we have . So one can write with being a positive integer. Then
[TABLE]
It then follows that
[TABLE]
for any subset with . So it follows from the first part that the received codeword is a deep hole of if . The second part is proved.
The proof of Theorem 1.5 is complete.
We can now present the proof of Theorem 1.7 as the conclusion of this paper.
Proof of Theorem 1.7. Letting and gives us that .
If , then by Theorem 1.5, one knows that the received word is a deep hole of the primitive projective Reed-Solomon code .
If , then it follows from that
[TABLE]
for any subset with . Hence is a deep hole of .
This completes the proof of Theorem 1.7.
The reference list from the paper itself. Each links out to its DOI / PubMed record.
- 1[1] Q. Cheng and E. Murray, On deciding deep holes of Reed-Solomon codes, Proc. T.A.M.C. 4484 (2007), 296-305.
- 2[2] A Dür, The decoding of extended Reed-Solomon codes, Discrete Math. 90 (1991), 21-40.
- 3[3] V. Guruswami and M. Sudan, Improved decoding of Reed-Solomon and algebraic-geometry codes, IEEE Trans. Inform. Theory 45 (1999), 1757-1767.
- 4[4] V. Guruswami and A. Vardy, Maximum-likelihood decoding of Reed-Solomon codes is NP-hard, IEEE Trans. Inform. Theory 51 (2005), 2249-2256.
- 5[5] S.F. Hong and R.J. Wu, On deep holes of generalized Reed-Solomon codes, AIMS Math. 1 (2016), 96-101.
- 6[6] J.Y. Li and D.Q. Wan, On the subset sum problem over finite fields, Finite Fields Appls. 14 (2008), 911-929.
- 7[7] Y.J. Li and D.Q. Wan, On error distance of Reed-Solomon codes, Science in China Series A: Mathematics 51 (2008), 1982-1988.
- 8[8] J.H. van Lint, Introduction to coding theroy (third edition), Springer-Verlag, Berlin, 1998.
