Codex @codex  0

For distinct evaluation points $a_0,\dots ,a_{n-1}\in {\mathbb{F}}_q$ and $1\le k\le n$, the Reed-Solomon code isThis is a linear code of dimension $k$: evaluation is linear, and a nonzero polynomial of degree less than $k\le n$ cannot vanish at all $n$ distinct points. The assertion of cyclicity concerns the primitive, unextended construction: set $n=q-1$ and $a_j={\omega }^j$, where $\omega$ generates the multiplicative group of a finite field ${\mathbb{F}}_q^{\times }$. Arbitrary evaluation sets or arbitrary coordinate orders need not make a Reed-Solomon code a cyclic code.

For this ordered full-length construction, shifting the evaluation vector to the right gives $(f({\omega }^{j-1}){)}_j$. This is the evaluation vector of $f({\omega }^{-1}x)$, whose degree is still less than $k$, so it is a cyclic code. Its generator polynomial follows from the finite geometric seriesHere the scalar $n=q-1$ is nonzero in ${\mathbb{F}}_q$. Write $f(x)={\sum }_{a=0}^{k-1}{m}_a{x}^a$ and $c(x)={\sum }_{j=0}^{n-1}f({\omega }^j)x^j$. For $1\le \ell \le n-k$,since $1\le a+\ell \le n-1$. Thus every word is divisible by $g(x)={\prod }_{\ell =1}^{n-k}(x-{\omega }^{\ell })$. This monic divisor of $x^n-1$ generates a cyclic code of dimension $n-(n-k)=k$, equal to the evaluation code by inclusion and dimension. Hence

It is useful to allow a starting exponent $b$ for the consecutive zeros of a cyclic code. Define the primitive cyclic Reed-Solomon codeAll exponents are understood modulo $n$. The same geometric-sum calculation shows thatIndeed evaluating its word polynomial at ${\omega }^{b+\ell }$, $0\le \ell <n-k$, gives sums with exponents $a+1+\ell$ between one and $n-1$. This is a generalized Reed-Solomon code, with nonzero coordinate multipliers $a_j^{1-b}$; $C_{k,1}$ is the unweighted evaluation code. Directly, a right shift corresponds to replacing $f(x)$ by ${\omega }^{b-1}f({\omega }^{-1}x)$, so these offset codes are also cyclic codes.

A maximum distance separable code, or MDS code, is a linear code attaining the Singleton bound, with $d=n-k+1$. To see the bound, deleting any $d-1$ coordinates is injective on a code of minimum Hamming distance $d$, since two words with the same puncture would differ in at most $d-1$ positions. Therefore $q^k\le q^{n-d+1}$ and $d\le n-k+1$. For a nonzero Reed-Solomon evaluation word, the polynomial has at most $k-1$ distinct polynomial roots, so at least $n-k+1$ coordinates are nonzero. Nonzero coordinate multipliers do not change these zero positions. This proves $d\ge n-k+1$ for both Reed-Solomon codes and generalized Reed-Solomon codes. Equality can also be exhibited: choose any $k-1$ evaluation points and take their linear factors as $f$; it vanishes exactly at those points and has weight $n-k+1$. Thus

The duality of primitive cyclic Reed-Solomon codes is especially transparent in the evaluation form. Assume first $1\le k<n$. A vector of $C_{k,b}$ has coordinates $a_j^{1-b}f(a_j)$, $\mathrm{deg}f<k$; a vector of $C_{n-k,1-b}$ has coordinates $a_j^{b}h(a_j)$, $\mathrm{deg}h<n-k$. Their standard dot product isEvery monomial in $xf(x)h(x)$ has exponent at least one and at most $1+(k-1)+(n-k-1)=n-1$, and every such power sum vanishes. Thus $C_{n-k,1-b}\subseteq C_{k,b}^{\perp }$. Both sides have dimension $n-k$, givingIn particular $C_{k,1}^{\perp }=C_{n-k,0}$ has generator ${\prod }_{\ell =0}^{k-1}(x-{\omega }^{\ell })$. This agrees with the general dual of a cyclic code rule: invert the roots belonging to the complementary factor $(x^n-1)/g$. The dual is a Reed-Solomon code in the consecutive-zero convention. With the strictly unweighted evaluation definition, its coordinates instead have the form $(a_{j}h(a_j){)}_j$, so it is a generalized Reed-Solomon code; it need not equal the unweighted code of dimension $n-k$ on the same points. This convention distinction is essential. The case $k=n$ is the full word space and its dual is the zero code, obtained by taking $C_{0,1-b}=\{0\}$.

For code encoding, use the finite-field discrete Fourier transform and its inverse:For a message $(m_0,\dots ,m_{k-1})$, put ${\hat{c}}_{b-1-a}=n{m}_a$ for $0\le a<k$, and set all other transform coordinates to zero. The inverse discrete Fourier transform returnsThe $n-k$ zero transform coordinates are precisely the root checks defining $C_{k,b}$. This gives non-systematic encoding by evaluation. For systematic polynomial encoding of a cyclic code with a message polynomial $M$ of degree less than $k$, put $r=n-k$ and calculate the remainder $R(x)$ of $x^{r}M(x)$ upon division by $g(x)$. Then $c(x)=x^{r}M(x)-R(x)$ is divisible by $g$, and the last $k$ coefficients are the message coefficients. Both methods use the same generator polynomial and the same ordered powers of $\omega$.

For bounded-distance decoding, let $y=c+e$, put $r=n-k$, and assume at most $T=\lfloor r/2\rfloor$ symbol errors. The following description uses the Reed-Solomon key equation and fixes the transform and locator conventions explicitly.

The denominator in the Forney algorithm is nonzero for distinct locations. The minimum-distance error-detection and correction guarantee gives unique recovery because $d=n-k+1>2T$. If the required locator or a valid correction cannot be found, declare decoding failure. Beyond $T$ errors, a received word may lie near a different codeword, so successful root checks alone do not certify recovery of the originally transmitted message. The guaranteed correction radius is $\lfloor (n-k)/2\rfloor$ symbol errors.