m | p | {{p^m}} | \delta_L |
1 | 3 | 0.159 | |
2 | 3 | 9 | 0.0385 |
3 | 27 | 0.011 | |
1 | 5 | 0.134 | |
2 | 5 | 25 | 0.022 |
3 | 125 | 0.00429 | |
1 | 7 | 0.118 | |
2 | 7 | 49 | 0.0148 |
3 | 343 | 0.002 |
This paper investigates double circulant codes of length 2n over Zpm where p is an odd prime, n goes to infinity, and m≥1 is a fixed integer. Using random coding, we obtain families of asymptotically good Lee codes over Zpm in the case of small and large alphabets, and asymptotically good Euclidean codes over Zpm for small alphabets. We use Euclidean codes to construct spherical codes, and Lee codes to construct insertion/deletion codes, by a projection technique due to (Yaglom, 1958) for spherical codes, and to (Sok et al., 2018) for deletion codes.
Citation: Adel Alahmadi, Altaf Alshuhail, Alaa Altassan, Hatoon Shoaib, Patrick Solé. Double circulant codes for the Lee and Euclidean distance[J]. AIMS Mathematics, 2023, 8(10): 23566-23577. doi: 10.3934/math.20231198
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This paper investigates double circulant codes of length 2n over Zpm where p is an odd prime, n goes to infinity, and m≥1 is a fixed integer. Using random coding, we obtain families of asymptotically good Lee codes over Zpm in the case of small and large alphabets, and asymptotically good Euclidean codes over Zpm for small alphabets. We use Euclidean codes to construct spherical codes, and Lee codes to construct insertion/deletion codes, by a projection technique due to (Yaglom, 1958) for spherical codes, and to (Sok et al., 2018) for deletion codes.
Double circulant codes over finite fields have been known to be asymptotically good for the Hamming distance for a long time [1,5]. The proof relies on a polynomial representation of double circulant codes, along with some number theoretic conjecture (Artin primitive root conjecture [13]). In general, the Hamming distance is not a natural metric for measuring error correction capabilities of codes over rings [14], or more generally of codes over alphabets of size >3, as attributing different weights to different nonzero symbols results into finer distances. For instance, the homogeneous metric is an important metric for ring alphabets. Thus, it was proved that double circulant codes over certain Galois rings are asymptotically good for the homogeneous distance [15].
In the present article, we shall consider double circulant codes over the rings Zpm where p is an odd prime, for the Lee and Euclidean distances, motivated by the following considerations.
The Lee metric is instrumental in constructing insertions/deletion codes [18] and the Euclidean metric is instrumental in constructing spherical codes [19]. In both cases, we use a projection technique due to Yaglom for spherical codes [11], and to [18] for insertion/deletion codes, that maps points within a ball in some dimension to the unit sphere in dimension one more. The Lee metric controls the Manhattan metric properties of lattices in constructed from codes over Zpm. Similarly, the Euclidean metric over ZNpm controls the standard Euclidean distance in the unit sphere of RN. For general background on, respectively, codes for the Lee metric, and codes for the Euclidean distance, we refer the reader respectively to [2,3] and to [7].
We derive the relative Manhattan distance and the rate of asymptotic growth for balls in the Manhattan metric when the ambient space dimension goes to infinity and the radius is fixed. We also derive the relative square Euclidean distance and the rate of spherical asymptotic growth for balls in the Euclidean metric when the radius and size go to infinity.
By expurgated random coding techniques, we derive a lower bound on the relative Lee (resp. Euclidean) distance of double circulant codes over the said rings. The counting arguments involved in the proof rely on the polynomial representation of quasi-cyclic codes, and their analysis via the CRT for polynomials developed in [11,12].
An outline of the paper is as follows. In Section 2, we provide some background material on Galois rings, Euclidean and Lee balls, and the algebraic structure of double circulant codes. Section 3 studies the asymptotic behavior of double circulant codes by the expurgated random coding argument made familiar by the Varshamov-Gilbert and Shannon bounds. Three cases are considered: Lee distance (small and large alphabets) and Euclidean distance. Section 4 concludes the article.
Throughout the paper, let p be an odd prime and m be a positive integer. The ring Zpm is the ring of integers modulo pm. The Galois ring GR(pm,pmn) of order pmn, and characteristic pm is the Galois extension of Zpm with degree n. It is a local ring, with maximal ideal ⟨p⟩. The Teichmüller set T={x∈GR(pm,pmn)∣xpn=x} of GR(pm,pmn) is a set of representatives of the residue field Fpn=GR(pm,pmn)/⟨p⟩. It is known that GR(pm,pmn)=T⊕pT⊕...⊕pm−1T so that any element x∈GR(pm,pmn) can be written as a base p decomposition of GR(pm,pmn), i.e., x=α0+pα1+...+pm−1αm−1 where αi∈T for 0⩽i<m. For motivation and background see [20].
A linear code C (for simply code) over Zq of length N is a submodule of ZNq. A code of length 2N is called double circulant over Zq if its generator matrix G is of the form G=(I,A), where I is the identity matrix of order N and A is a circulant matrix over Zq of the same order.
The Zq-module ZNq is equipped with three natural distances [4] that we describe in the following three paragraphs.
The Hamming distance between two codewords in C is the number of places where they differ, and it is denoted by dH. The Hamming weight of any codeword in C is the number of nonzero components, and is denoted by wH.
The Lee weight of an element h∈Zq viewed as an integer ∈[0,q) is defined as follows:
wL(h)=min{h,q−h}. |
The Lee weight of vectors ZNq (codewords in C) is the sum of Lee weight of its components. The Lee distance dL between two integers h1,h2∈Zq is the Lee weight of h1−h2. The Lee distance dL between two vectors in ZNq (codewords in C), is the sum of the Lee distances between their corresponding components.
In [2], it is shown that the Lee weight of any nonzero vector x∈ZNpm is bounded from above and below as follows:
wH(x)≤wL(x)≤(pm−12)wH(x). | (2.1) |
The Euclidean weight of any element h in Zq can be defined directly as
wE(h)=min(h2,(q−h)2)=wL(h)2. | (2.2) |
This notion can be extended to vectors in the obvious way, and the Euclidean distance between two vectors x and y on ZNq is then defined as dE(x,y)=wE(x−y). The minimum Euclidean distance dE of a code C is then given by
dE=min{dE(ci,cj)∣ci,cj∈C, and ci≠cj}. |
As in [19], if q=2s+1, we will define the addressing map ϕ from Zq into R by
ϕ(h)={hif h≤s,−(q−h)if h>s. |
This map can be extended to vectors in the obvious way.
We remark that the Euclidean distance between two vectors x and y on ZNq satisfy the property
dE(x,y)=(ϕ(x)−ϕ(y))2. |
Following [18], we define the Manhattan distance between two vectors x,y∈ZN as
d1(x,y)=N∑i=1|xi−yi|. |
Define an (N,d1,N,r)− code as a set of vectors of Zn, with pairwise Manhattan distance at least d1, every coordinate at least r, and total sum of entries equal to N. The addressing map Yr to the ring Zq uses the coset representatives r,r+1,…,r+q−1 of qZ into Z. We introduce a map ΥN from ZN to ZN+1 defined by
ΥN(x)=(x1,…,xN,N−N∑i=1xi). |
Note that N=∑Ni=1Yr(xi).
Proposition 1. If C is a code over Zq of length N and minimum Lee distance dL over Zq, with the addressing Yr, and N−N(q+r−1)>r, then ΥN∘Yr(C) is an (N+1,d1,N,r)− code in ZN+1 where its Manhattan distance is bounded below by the Lee distance of C.
The coordinates of each codeword are at least r by Definition of Yr. The last coordinate of the ΥN image is also ≥r because ∑Ni=1xi≤N(q+r−1). The total sum of the entries of the ΥN image is N by Definition of ΥN. The pairwise Manhattan distance of codewords is at least d1, because the Manhattan distance is bounded below by the Lee distance. Note that the ΥN adds an extra entry to vectors which can only increase the Manhattan distance.
In this section we use [7], the ball of radius e in Euclidean N-space RN is the set defined as
B(N,e)={(x1,x2,...,xN)∈RN|N∑i=1x2i⩽e2}. |
The sphere of radius e in Euclidean N-space RN is the set defined as
S(N,e)={(x1,x2,...,xN)∈RN|N∑i=1x2i=e2}. |
When e=1, S(N,1) is called the unit sphere. A spherical code X is a finite subset of S(N,1). The squared minimum distance ρ is the smallest squared distance between pairs of distinct codewords:
ρ(x,y)=min{N∑i=1(xi−yi)2|x=(x1,x2,...,xN),y=(y1,y2,...,yN)∈X,x≠y}. |
Following [19], we embed RN into RN+1 by the Yaglom map
Y:(x1,...,xN)↦(x1,...,xN,√e2−N∑i=1xi2). |
Note that this map sends the ball B(N+1,e) of radius e in RN into the sphere S(N+1,e) with radius e in RN+1.
Proposition 2. [19] Let q=2s+1. If C is a code of length N and minimum Euclidean distance dE over Zq, then Y(ϕ(C)) is a spherical code lying in the sphere S(N,s√N) of squared Euclidean distance dE.
From now on, we assume that n is an odd integer, and gcd(n,pm)=1. We can cast the factorization of xn−1 into distinct basic irreducible polynomials over Zpm in the form
xn−1=μ(x−1)u∏i=2gi(x)t∏i=1hi(x)h∗i(x), | (2.3) |
where μ nonzero unit in Zpm, gi(x) is a self-reciprocal polynomial with degree 2ei for 2≤i≤u, and h∗j(x) is the reciprocal polynomial of hj(x) with degree bj for 1≤j≤t. By the Chinese Remainder Theorem (CRT), we have
Zpm[x]⟨xn−1⟩≃Zpm[x]⟨x−1⟩⊕(u⨁i=2Zpm[x]⟨gi(x)⟩)⊕t⨁j=1(Zpm[x]⟨hj(x)⟩⊕Zpm[x]⟨h∗j(x)⟩)≃Zpm⊕(u⨁i=2GR(pm,p2mei))⊕(t⨁j=1GR(pm,pmbj)⊕GR(pm,pmbj)). |
Note that all of these rings are extensions of Zpm. Let Rn=Zpm[x]⟨xn−1⟩. This decomposition naturally extends to R2n as follows
R2n⋍Z2pm⊕(u⨁i=2GR(pm,p2mei)2)⊕(t⨁j=1(GR(pm,pmbj))2⊕GR((pm,pmbj))2). |
In particular, each linear code C of length 2 over Zpm can be decomposed as the -CRT sum-
C=C1⊕u⨁i=2Ci⊕t⨁j=1(C′j⊕Cj″ |
So {{\mathcal C}} can be viewed as a submodule of \mathcal{R}_n^2 , with generator \langle 1, a(x)\rangle , where the x - expansion of a(x) \in \mathbb{Z}_{p^m}[x] is the first row of A .
Let {{\mathcal C}} be a code of length N over \mathbb{Z}_{p} . This code is linear if it is a \mathbb{Z}_{p} -vector subspace of \mathbb{Z}_{p}^N . The dimension of a code {{\mathcal C}} , denoted by k , is equal to its dimension as a vector space.
The three parameters of a code are written compactly as [N, k, d_H] , [N, k, d_L] or [N, k, d_E], depending on the distance considered. When we extend this notation to code {{\mathcal C}} that is a submodule of \mathbb{Z}_{q}^N , then k = \log_{q}(|{{\mathcal C}}|) where |{{\mathcal C}}| is the number of codewords in {{\mathcal C}} . Let {{\mathcal C}}(N) be a family of codes with parameters [N, k_N] . The rate of {{\mathcal C}}(N) is defined to be R = \limsup_{N\rightarrow \infty} \frac{k_N}{N} . The relative minimum distance \delta depends on the third parameters as follows:
Remark 3. Let s = \frac{q-1}{2} . If {{\mathcal C}}(N) a family of codes with the following distances:
(i) Hamming distance d_{H, N} , then its relative Hamming distance is \delta_H = \liminf_{N\rightarrow \infty} \frac{d_{H, N}}{N} .
(ii) Lee distance d_{L, N} , then is its relative Lee distance is \delta_L = \liminf_{N\rightarrow \infty} \frac{d_{L, N}}{s N} .
(iii) Euclidean distance d_{E, N} , then its relative Euclidean distance is \delta_E = \liminf_{N\rightarrow \infty} \frac{d_{E, N}}{s^2 N} .
A family of codes is said to be good if R \delta \neq 0 .
Let V_L(N, e, q) (resp. V_E(N, e, q) ) denote the size of the Lee (resp. Euclidean) sphere of radius e , and let us define A_L(N, d_L, q) (resp. A_E(N, d_E, q) ) to be the maximal number of codewords in a code of length N over \mathbb{Z}_{q} with Lee (resp. Euclidean) distance d_L (resp. d_E ).
The following Theorem is the analogue of the standard Gilbert bound of the Hamming metric in the Lee and Euclidean metric. The standard proof is omitted.
Theorem 4. There are codes in \mathbb{Z}_{q}^N of Lee distance d_L and of cardinality
\begin{eqnarray*} A_L(N, d_L, q) &\geq& \frac{q^{N}}{V_L(N, d_L-1, q)}. \end{eqnarray*} |
There are codes in \mathbb{Z}_{q}^N of Euclidean distance d_E and of cardinality
\begin{eqnarray*} A_E(N, d_E, q) &\geq& \frac{q^{N}}{V_E(N, d_E-1, q)}. \end{eqnarray*} |
The following three theorems give the asymptotic exponent of V_L(N, e, q) (resp. V_E(N, e, q) ) for N large and e = s \tau N , where 0 \leq \tau \leq 1 , and with the standard definition of the rate and relative minimum distance of the family of codes {{\mathcal C}}(N) . Their respective corollaries are the analogues of the classical Asymptotic Gilbert-Varshamov Bound [9] for, respectively, the Lee distance (first small alphabets, then large alphabets) or the Euclidean distance. For simplicity'sake we concentrate on the case of p odd.
If we denote
\begin{eqnarray*} l(\tau, q)& = &\lim\limits_{N \rightarrow \infty}(1-\frac{1}{N} \log_q(V_L(N, s \tau N , q))), \end{eqnarray*} |
where 0 \leq \tau \leq 1 .
Theorem 5. [3] If q = 2s+1 , then l(\tau, q) = 1+\log_q\alpha\beta^{s\tau} , where \alpha \geqslant 0, \beta \geqslant 0 satisfy
\begin{eqnarray*} \alpha+2\alpha\sum\limits_{i = 1}^{s}\beta^i& = &1, \\ \alpha\sum\limits_{i = 1}^{s}i\beta^i& = &\frac{\tau.s}{2}, \end{eqnarray*} |
where 0 \leqslant \tau \leqslant (q+1)/2q . Moreover, l(\tau, q) = 0 if (q+1)/2q \leqslant \tau \leqslant 1 .
Corollary 6. [3] If 0 < \delta_L \leq \frac{q+1}{2q} where q \geq 2 , then
\begin{eqnarray*} R &\geq& l(\delta_L, q) \end{eqnarray*} |
where R = \liminf_{n \mapsto \infty }\frac{1}{n} \log_q A_L(n, s\delta_L n, q) .
Theorem 7. [19] For q\geqslant 2r+1 , for large N and \frac{r}{N} tending to \omega , we obtain
\begin{eqnarray*} \lim\limits_{N \rightarrow \infty}\frac{1}{N} \log_q(V_L(N, e, q))& = & L_q(\omega) + o(1), \end{eqnarray*} |
where
L_q(x) = x \log_q(x)+\log_q(x+\sqrt{x^2+1})-x \log_q(\sqrt{x^2+1}-1). |
Corollary 8. [19] If 0 < \delta_L \leq L_q(1) where q \geq {2 \delta_L} N + 1 , then
\begin{eqnarray*} R &\geq& 1- L_q(\delta_L). \end{eqnarray*} |
Theorem 9. [8] The asymptotic exponent of V_E(N, e, q) for N large and e = \lfloor \tau N\rfloor is
\begin{eqnarray*} \lim\limits_{N \rightarrow \infty}\frac{1}{N} \log_q(V_E(N, r, q)) = E(\tau, q), \end{eqnarray*} |
where E(\tau, q) = \log_q(f(\mu))- \tau \log_q(\mu) and \mu is the unique real positive solution of z f'(z) = \tau f(z) , and f(z) = 1+2\sum_{i = 1}^{s} z^{i^2} .
Corollary 10. [8] If 0 < \delta_E \leq 1- \frac{1}{q} where q = 2s+1 , then
\begin{eqnarray*} R &\geq& 1- E(s^2\delta_E, q). \end{eqnarray*} |
This section is only for the special case of the factorization of x^n-1 over \mathbb{Z}_{p^m} into exactly two basic irreducible polynomials. In particular, for m = 1, the existence of such a factorization for infinitely many n' s will depend on Artin primitive root conjecture, which is known to hold under Generalized Riemann Hypothesis (GRH), and is proved by Hath-Brown for all but a finite number of primes [13]. Lifting such a factorization, for fixed n, from \mathbb{F}_p to \mathbb{Z}_{p^m} is ensured by Hensel lifting [20]. Let \mathcal{C}_a denotes the double circulant code generated by \langle1, a\rangle , where a = a(x) is a polynomial in \mathbb{Z}_{p^m}[x] .
Theorem 11. From the above assumptions. If f, g \in \mathbb{Z}_{p^m}^{n} such that (0, 0)\neq (f, g) , and (f, g) has Lee weight less than n , then the vector (f, g) gives at most \lambda double circulant codes over \mathbb{Z}_{p^m} of length 2n with \lambda = p^{(m-1)n+1} .
By the CRT, (f, g)\simeq (f_1, g_1)\oplus(f_2, g_2) where f_1 and g_1 = a_1 f_1 as elements of \mathbb{Z}_{p^{m}} , f_2 and g_2 = a_2 f_2 as elements of GR(p^m, p^{m(n-1)}) . Consider \mathcal{C}_{a_1} = \langle[1, a_1]\rangle , and \mathcal{C}_{a_2} = \langle[1, a_2]\rangle . Let (f_1, g_1)\in \mathcal{C}_{a_1} and (f_2, g_2)\in \mathcal{C}_{a_2} . Determining a is equivalent to determining the pair (a_1, a_2) .
We distinguish the following cases:
ⅰ. If f_1 is a unit, then a_1 is uniquely determined by g_1 = a_1f_1 .
ⅱ. If (f_1 \neq 0) is not a unit, where f_1 = p^hf'_1 such that f'_1 is a unit and 1 \leq h \leq m-1 , we then obtain g_1 = p^h g^\ast where g^\ast \in \mathbb{Z}_{p^m} , which implies a_1 f'_1-g^\ast = p^{m-h} \alpha where \alpha = \sum_{i = 0}^{h-1}\alpha_i p^i . Each \alpha_i for 0 \leq i \leq h-1 can take at most {p} values. So a_1 takes at most p^h \leq p^{(m-1)} values.
ⅲ. If f_1 = 0 , then a_1 can take at most p^m values.
{\rm{iii}}-1. If f_2 = 0 , then (f, g) = (0, 0) , a contradiction as (f, g) is a nonzero vectors.
{\rm{iii}}-2. If f_2 is a unit then a_2 is uniquely determined by the equation g_2 = a_2f_2 . So a has p^{m} values.
{\rm{iii}}-3. If f_2 \neq 0 is not a unit, the case is similar to that of f_1 with \alpha having at most p^{h(n-1)} values by the p -adic representation in GR(p^m, p^{m(n-1)}) . Thus a_2 has at most p^{(n-1)(m-1)} since h\leq m-1 . It follows that a has p^{m}p^{(m-1)(n-1)} values.
ⅳ. If f_1\neq 0 and f_2\neq 0 are not units, then by (\text{ii}) and (\text{iii-3}) a has at most p^{n(m-1)} values.
ⅴ. If f_1\neq 0 and f_2\neq 0 are units, then a = \frac{g}{f} has a unique solution.
ⅵ. If f_1\neq 0 is not a unit and f_2 = 0 , we then obtain w_H(f) = n , and by (1.4.1) we have w_L((f, g)) > n , a contradiction with the hypothesis.
Thus, we obtain that there are at most \lambda = p^mp^{(m-1)(n-1)} = p^{n(m-1)+1} double circulant codes over \mathbb{Z}_{p^m} of length 2n .
The following results use that fact that the volumes of Lee balls for (large and small alphabets) with radius s\delta_0 N are, up to subexponential terms, p^{Nm(L_{{p^m}}(s.\delta_0) + o(1))} (resp. p^{Nm(1-l(\delta_0, {{p^m}}))} ), when 0 < \delta_0 < 1 and N go to infinity.
Theorem 12. Let p = 2s+1 and p^m \geqslant 2a+1 with a = 2sn\delta_0 such that \delta_0 \in(0, 1) . Then the family of double circulant codes over \mathbb{Z}_{p^m} with length 2n , rate \frac{1}{2} , and relative distance \delta_L , satisfies \delta_L \geq L^{-1}_{{p^m}}(\frac{1}{2m})s^{-1} . In particular, that family of codes is good.
Let {{p^m}} = 2s+1 be fixed, and let \Omega_n denote the size of the family of double circulant codes over \mathbb{Z}_{p^m} of length 2n . Thus, for n\rightarrow \infty we have \Omega_n \sim p^{mn} . Assume we can prove that for n large enough \Omega_n > \lambda_n V(2n, d_{L, n}, {{p^m}}) . Here \lambda_n = p^{n(m-1)+1} . This would imply, by Theorem 11, that there are double circulant codes of length 2n in the family with minimum Lee distance greater than or equal d_{L, n} . Let \delta_L be the relative Lee distance of this family. If we take d_{L, n} to be the largest number satisfying \Omega_n > \lambda_n V(2n, d_{L, n}, {{p^m}}) , and assume a growth of the form d_{L, n}\sim 2 s n \delta_o , then \Omega_n \sim \lambda_n V(2n, d_{L, n}, {{p^m}}) for n\rightarrow \infty using the large alphabets entropic estimate for V_L(2n, d_{L, n}, {{p^m}}) \sim p^{2nm(L_p(s\delta_o)+o(1))} , with values of \Omega_n and \lambda_n , with the estimate {\delta_o} = L^{-1}_{{p^m}}(\frac{1}{2m})s^{-1} . The result follows by observing that, by definition of \delta_L , \delta_L \geq \delta_o .
The next Theorem follows by using a similar argument as in the proof of Theorem 12.
Theorem 13. Let {{p^m}} = 2s+1 . Then the family of double circulant codes over \mathbb{Z}_{p^m} of length 2n , and rate \frac{1}{2} , of relative distance \delta_L , satisfies \delta_L \geq l^{-1}(\frac{2m-1}{2m}, {{p^m}}) . In particular, that family of codes is good.
By [8], assume that d^1, r are fixed, \mathcal{{N}} \rightarrow \infty , and n \sim \eta \mathcal{{N}} /r , for some constant \eta \in (0, 1) . Denote by R^1 the asymptotic rate of a family of (2n, d^1, \mathcal{{N}}, r) -codes {{\mathcal C}}_n , and the rate is given as follows
\begin{eqnarray*} R^1& = &\limsup\limits_{\mathcal{{N}} \rightarrow \infty}\frac{1}{\mathcal{{N}}} \log_2 |{{\mathcal C}}_n|. \end{eqnarray*} |
Corollary 14. There is a family of (2n+1, d^1, {{N}}, r) -codes over \mathbb{Z} of relative Manhattan distance at least l^{-1}(\frac{2m-1}{2m}, {{p^m}}) , and rate R^1 , which satisfies R^1 = \frac{\eta m}{r} \log_2p .
Let d^1, r be fixed, by Theorem 13, there is a family of double circulant codes {{\mathcal C}} denoted by \Omega_n over \mathbb{Z}_{p^m} of length 2n and of Lee distance at least d_L and by Proposition 1, there is a family of (2n+1, d^1, \mathcal{N}, r) - codes up to normalization \Upsilon_{\mathcal{N}}(Y_r({{\mathcal C}})) of \mathbb{Z}^{2n+1} , and its rate satisfies R^1 = \frac{1}{\mathcal{{N}}} \log_2p^{mn} \Rightarrow R^1 = \frac{\eta m}{r} \log_2p .
In Table 1, values of \delta_L are listed for some values of {{p^m}} . If {{\mathcal C}}(n) is a family of codes of parameters [n, k_n, d_{L, n}] , then by Corollary 14 l(\delta_L, {{p^m}}) = \frac{2m-1}{2m} .
m | p | {{p^m}} | \delta_L |
1 | 3 | 0.159 | |
2 | 3 | 9 | 0.0385 |
3 | 27 | 0.011 | |
1 | 5 | 0.134 | |
2 | 5 | 25 | 0.022 |
3 | 125 | 0.00429 | |
1 | 7 | 0.118 | |
2 | 7 | 49 | 0.0148 |
3 | 343 | 0.002 |
Theorem 15. If f, g \in \mathbb{Z}_{p^m}^n such that (f, g)\neq (0, 0) , and (f, g) has Euclidean weight less than n , then there are at most p^{(m-1)n+1} polynomials a such that (f, g)\in \mathcal{C}_a .
We can prove this result in the same manner as Theorem 11. By using Eqs (2.1) and (2.2), we get w_H \leqslant w_L \leqslant w_E . It follows that there are at most p^{(m-1)n+1} polynomials a such that (f, g) \in {{\mathcal C}}_a .
Theorem 16. Let {{p^m}} = 2s+1 . Then the family of double circulant codes over \mathbb{Z}_{p^m} of length 2n , rate \frac{1}{2} , and relative distance \delta_E , satisfies \delta_E \geq E^{-1}(\frac{1}{2m}, p)\cdot s^{-2} . In particular, these families of codes are good.
By applying Theorem 9 in the case where the radius of the Euclidean sphere is 2s\delta_E n , and using a similar technique to the proof of Theorem 12 the result follows.
In Table 2, values of \delta_E are listed for some values of {{p^m}} . If {{\mathcal C}}(n) is a family of Euclidean codes of parameters [n, k_n, d_{E, n}] , then by Theorem 16 E(s^2 \cdot \delta_E, {{p^m}}) = \frac{1}{2m} .
m | p | {{p^m}} | \delta_E |
1 | 3 | 0.159 | |
2 | 3 | 9 | 0.996 \times 10^{-2} |
3 | 27 | 0.943 \times 10^{-3} | |
1 | 5 | 0.723 | |
2 | 5 | 25 | 0.996 \times 10^{-2} |
3 | 125 | 0.753 \times 10^{-4} | |
1 | 7 | 0.454 \times 10^{-2} | |
2 | 7 | 49 | 0.710 \times 10^{-3} |
3 | 343 | 0.139 \times 10^{-4} |
Following [6], let R denotes the asymptotic binary rate of a family of spherical codes \mathcal{X} , and the rate is given as follows
\begin{eqnarray} R& = & \lim\limits_{N\rightarrow \infty} \frac{\log_2(|\mathcal{X}|)}{N}. \end{eqnarray} | (3.1) |
In [10] a lower bound of Shannon is given a lower bound on the binary rate of a spherical code R_{S} of a given 0 \leq \tau \leq 1
\begin{eqnarray} R \leq R_S(\tau ) & = &1-\frac{1}{2}\log_2(\tau (4-\tau )). \end{eqnarray} | (3.2) |
From Theorem 16 and Proposition 2, the following corollary immediately follows.
Corollary 17. Let {{p^m}} = 2s+1 . There is a family of spherical codes up to normalization Y(\phi({{\mathcal C}})) of \mathbb{R}^{2n+1} , binary rate \frac{{m}\log_2 p}{2} , and relative squared distance \delta_E \geq {E^{-1}(\frac{1}{2m}, p) s^{-2}} .
In Table 3 is shown that comparison between R(\delta_E) and R_S(\delta_E) where \delta_E is given in previous corollary.
m | p | {{p^m}} | \delta_E | R | R_{S}(\delta_E) |
1 | 3 | 0.159 | 0.792 | 1.353 | |
2 | 3 | 9 | 0.996 \times 10^{-2} | 1.584 | 3.326 |
3 | 27 | 0.943 \times 10^{-3} | 2.377 | 5.0252 | |
1 | 5 | 0.723 | 1.160 | 1.907 | |
2 | 5 | 25 | 0.996 \times 10^{-2} | 2.321 | 3.326 |
3 | 125 | 0.753 \times 10^{-4} | 3.482 | 6.848 | |
1 | 7 | 0.454 \times 10^{-2} | 1.403 | 2.237 | |
2 | 7 | 49 | 0.710 \times 10^{-3} | 2.807 | 5.229 |
3 | 343 | 0.139 \times 10^{-4} | 4.211 | 8.0621 |
In this paper we have proved the existence of asymptotically good families of double circulant codes for the Lee distance and the Euclidean distance. The motivation was to construct spherical codes from Euclidean distance codes and insertions/deletion codes in the case of the Lee distance. There are certainly some more applications in the domain of Euclidean lattices, or lattices for the Manhattan metric obtained from codes by the so-called Construction A [11]. At a more technical level, considering quasi-cyclic codes of index higher than 2, extending these results to three- and four-circulant codes and to their negacirculant counterparts following the paths in [16,17] is a worthwhile project.
The authors declare they have not used Artificial Intelligence (AI) tools in the creation of this article.
This project was funded by the Deanship of Scientific Research (DSR), King Abdulaziz University, Jeddah, Saudi Arabia under grant no. (KEP-Msc-28-130-40). The authrs, therefore, acknowledge with thanks DSR techical and financial support.
Prof. Patrick Solé is the Guest Editor of special issue "Mathematical Coding Theory and its Applications" for AIMS Mathematics. Prof. Patrick Solé was not involved in the editorial review and the decision to publish this article.
All authors declare no conflicts of interest in this paper.
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m | p | {{p^m}} | \delta_L |
1 | 3 | 0.159 | |
2 | 3 | 9 | 0.0385 |
3 | 27 | 0.011 | |
1 | 5 | 0.134 | |
2 | 5 | 25 | 0.022 |
3 | 125 | 0.00429 | |
1 | 7 | 0.118 | |
2 | 7 | 49 | 0.0148 |
3 | 343 | 0.002 |
m | p | {{p^m}} | \delta_E |
1 | 3 | 0.159 | |
2 | 3 | 9 | 0.996 \times 10^{-2} |
3 | 27 | 0.943 \times 10^{-3} | |
1 | 5 | 0.723 | |
2 | 5 | 25 | 0.996 \times 10^{-2} |
3 | 125 | 0.753 \times 10^{-4} | |
1 | 7 | 0.454 \times 10^{-2} | |
2 | 7 | 49 | 0.710 \times 10^{-3} |
3 | 343 | 0.139 \times 10^{-4} |
m | p | {{p^m}} | \delta_E | R | R_{S}(\delta_E) |
1 | 3 | 0.159 | 0.792 | 1.353 | |
2 | 3 | 9 | 0.996 \times 10^{-2} | 1.584 | 3.326 |
3 | 27 | 0.943 \times 10^{-3} | 2.377 | 5.0252 | |
1 | 5 | 0.723 | 1.160 | 1.907 | |
2 | 5 | 25 | 0.996 \times 10^{-2} | 2.321 | 3.326 |
3 | 125 | 0.753 \times 10^{-4} | 3.482 | 6.848 | |
1 | 7 | 0.454 \times 10^{-2} | 1.403 | 2.237 | |
2 | 7 | 49 | 0.710 \times 10^{-3} | 2.807 | 5.229 |
3 | 343 | 0.139 \times 10^{-4} | 4.211 | 8.0621 |
m | p | {{p^m}} | \delta_L |
1 | 3 | 0.159 | |
2 | 3 | 9 | 0.0385 |
3 | 27 | 0.011 | |
1 | 5 | 0.134 | |
2 | 5 | 25 | 0.022 |
3 | 125 | 0.00429 | |
1 | 7 | 0.118 | |
2 | 7 | 49 | 0.0148 |
3 | 343 | 0.002 |
m | p | {{p^m}} | \delta_E |
1 | 3 | 0.159 | |
2 | 3 | 9 | 0.996 \times 10^{-2} |
3 | 27 | 0.943 \times 10^{-3} | |
1 | 5 | 0.723 | |
2 | 5 | 25 | 0.996 \times 10^{-2} |
3 | 125 | 0.753 \times 10^{-4} | |
1 | 7 | 0.454 \times 10^{-2} | |
2 | 7 | 49 | 0.710 \times 10^{-3} |
3 | 343 | 0.139 \times 10^{-4} |
m | p | {{p^m}} | \delta_E | R | R_{S}(\delta_E) |
1 | 3 | 0.159 | 0.792 | 1.353 | |
2 | 3 | 9 | 0.996 \times 10^{-2} | 1.584 | 3.326 |
3 | 27 | 0.943 \times 10^{-3} | 2.377 | 5.0252 | |
1 | 5 | 0.723 | 1.160 | 1.907 | |
2 | 5 | 25 | 0.996 \times 10^{-2} | 2.321 | 3.326 |
3 | 125 | 0.753 \times 10^{-4} | 3.482 | 6.848 | |
1 | 7 | 0.454 \times 10^{-2} | 1.403 | 2.237 | |
2 | 7 | 49 | 0.710 \times 10^{-3} | 2.807 | 5.229 |
3 | 343 | 0.139 \times 10^{-4} | 4.211 | 8.0621 |