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Introduction

In abstract algebra, Chien's search is a recursive algorithm

for determining roots of polynomials defined over a finite field.

The most typical use of Chien's search is in finding the roots of

error-locator polynomials encountered in decoding

Reed-Solomon codes and BCH codes.

 

Algorithm

We denote the polynomial whose roots we wish to determine as

\ \Lambda(x) = \lambda_0 + \lambda_1 x + \lambda_2 x^2 + \ldots + \lambda_t x^t

Conceptually, we may evaluate \ \Lambda(\beta) for each

non-zero \ \beta in our finite field GF(q).

Those resulting in 0 are roots of the polynomial.

Chien's search is based on two observations:

  • Each non-zero \ \beta may be expressed as \ \alpha^{i_\beta} for some \ i_\beta
  • where \ \alpha is the primitive element of GF(q).
  •  
  • Therefore, the powers \ \alpha^i for \ 0 \leq i < (N-1)
  • cover the entire field (excluding the zero element).
  •  
  • The following relationship exists:

\begin{array}{lllllllllll}
 \Lambda(\alpha^i) &=& \lambda_0 &+& \lambda_1 \alpha^i &+& \lambda_2 (\alpha^i)^2 &+& \ldots &+& \lambda_t (\alpha^i)^t  \\
                   &\triangleq& \gamma_{0,i} &+& \gamma_{1,i} &+& \gamma_{2,i} &+& \ldots &+& \gamma_{t,i}
\end{array}

\begin{array}{lllllllllll}
 \Lambda(\alpha^{i+1}) &=& \lambda_0 &+& \lambda_1 \alpha^{i+1} &+& \lambda_2 (\alpha^{i+1})^2 &+& \ldots &+& \lambda_t (\alpha^{i+1})^t  \\
                       &=& \lambda_0 &+& \lambda_1 (\alpha^i)\,\alpha &+& \lambda_2 (\alpha^i)^2\,\alpha^2 &+& \ldots &+& \lambda_t (\alpha^i)^t\,\alpha^t  \\
                       &=& \gamma_{0,i} &+& \gamma_{1,i}\,\alpha &+& \gamma_{2,i}\,\alpha^2 &+& \ldots &+& \gamma_{t,i}\,\alpha^t \\
                   &\triangleq& \gamma_{0,i+1} &+& \gamma_{1,i+1} &+& \gamma_{2,i+1} &+& \ldots &+& \gamma_{t,i+1}
\end{array}
     

In other words, we may define each \ \Lambda(\alpha^i)

as the sum of a set of terms \ \{\gamma_{j,i} | 0\leq j \leq t\},

from which the next set of coefficients may be derived thus:

\ \gamma_{j,i+1} = \gamma_{j,i}\,\alpha^i

In this way, we may start at \ i = 0 with \ \gamma_{j,0} = \lambda_j

and iterate through each value of \ i up to \ (N-1).

If at any stage the resultant summation is zero, i.e.

\ \sum_{j=0}^t \gamma_{j,i} = 0

then \ \Lambda(\alpha^i) = 0 also, so \ \alpha_i is a root.

In this way, we check every element in the field.

When implemented in hardware,

this approach significantly reduces the complexity,

as all multiplications consist of one variable and one constant,

rather than two variables as in the brute-force approach.

References

  • R.T. Chien, "Cyclic Decoding Procedure for the
  • Bose-Chaudhuri-Hocquenghem Codes,"
  • IEEE Transactions on Information Theory,
  • Vol. IT-10, pp. 357-363, October 1964.
  •  
  • S. Lin and D. Costello. Error Control Coding:
  • Fundamentals and Applications.
  • Prentice-Hall, Englewood Cliffs, NJ, 2004.
 
 

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