I need to find parameters $n$, $k$ and $d$ of a binary linear code from its Generator Matrix.
How can I find parameter $d$ efficiently?
I know the method that compute all the codewords and take minimum non-zero weight code will be the minimum distance. but it's an exponential time algorithm. Is there any efficient algorithm to do the same?
Best Answer
As pointed out by Snowball, the problem is inherently hard, see also this paper.
However, it can be done much faster in general than generating all the codewords.
I explain the idea for linear $[n,k]$ codes $C$ with $n = 2k$. First, we construct two generator matrices $G_1 = (I\ A)$ and $G_2 = (B\ I)$ of $C$ where $I$ is the $(k\times k)$ unit matrix and $A,B$ are two $(k\times k)$ matrices. This is only possible if the positions $1,\ldots,k$ and $k+1,\ldots n$ form two information sets of $C$. If this is not the case, we have to find a suitable coordinate permutation first.
Now a codeword of weight $w$ has weight at most $\lfloor w/2\rfloor$ either in the first or in the second $n$ coordinates. Thus, we can find all codewords of weight $\leq w$ among the codewords $x G_1 = (x, xA)$ and $x G_2 = (Bx, x)$, where $x$ is a vector of length $k$ and Hamming weight at most $\lfloor w/2\rfloor$. So we can find the minimum distance $d$ of $C$ if we do this iteratively for all $w = 1,2,3,\ldots, d$.
In this way, you have to generate only a small fraction of all the codewords to find the minimum distance, and the idea can be generalized to any linear code. The first step then is to find a covering of the coordinates with information sets. However, the algorithm is still exponential, of course.
The webpage codetables.de is a valuable source for bounds on the best known minimum distances for fixed $q$, $n$ and $k$.