Generator matrix
In coding theory, a generator matrix is a matrix whose rows form a basis for a linear code. The codewords are all of the linear combinations of the rows of this matrix, that is, the linear code is the row space of its generator matrix.
Terminology
[edit]If G is a matrix, it generates the codewords of a linear code C by
where w is a codeword of the linear code C, and s is any input vector. Both w and s are assumed to be row vectors.[1] A generator matrix for a linear -code has format , where n is the length of a codeword, k is the number of information bits (the dimension of C as a vector subspace), d is the minimum distance of the code, and q is size of the finite field, that is, the number of symbols in the alphabet (thus, q = 2 indicates a binary code, etc.). The number of redundant bits is denoted by .
The standard form for a generator matrix is,[2]
- ,
where is the identity matrix and P is a matrix. When the generator matrix is in standard form, the code C is systematic in its first k coordinate positions.[3]
A generator matrix can be used to construct the parity check matrix for a code (and vice versa). If the generator matrix G is in standard form, , then the parity check matrix for C is[4]
- ,
where is the transpose of the matrix . This is a consequence of the fact that a parity check matrix of is a generator matrix of the dual code .
G is a matrix, while H is a matrix.
Equivalent codes
[edit]Codes C1 and C2 are equivalent (denoted C1 ~ C2) if one code can be obtained from the other via the following two transformations:[5]
- arbitrarily permute the components, and
- independently scale by a non-zero element any components.
Equivalent codes have the same minimum distance.
The generator matrices of equivalent codes can be obtained from one another via the following elementary operations:[6]
- permute rows
- scale rows by a nonzero scalar
- add rows to other rows
- permute columns, and
- scale columns by a nonzero scalar.
Thus, we can perform Gaussian elimination on G. Indeed, this allows us to assume that the generator matrix is in the standard form. More precisely, for any matrix G we can find an invertible matrix U such that , where G and generate equivalent codes.
See also
[edit]Notes
[edit]- ^ MacKay, David, J.C. (2003). Information Theory, Inference, and Learning Algorithms (PDF). Cambridge University Press. p. 9. ISBN 9780521642989.
Because the Hamming code is a linear code, it can be written compactly in terms of matrices as follows. The transmitted codeword is obtained from the source sequence by a linear operation,
where is the generator matrix of the code... I have assumed that and are column vectors. If instead they are row vectors, then this equation is replaced by
... I find it easier to relate to the right-multiplication (...) than the left-multiplication (...). Many coding theory texts use the left-multiplying conventions (...), however. ...The rows of the generator matrix can be viewed as defining the basis vectors.{{cite book}}
: CS1 maint: multiple names: authors list (link) - ^ Ling & Xing 2004, p. 52
- ^ Roman 1992, p. 198
- ^ Roman 1992, p. 200
- ^ Pless 1998, p. 8
- ^ Welsh 1988, pp. 54-55
References
[edit]- Ling, San; Xing, Chaoping (2004), Coding Theory / A First Course, Cambridge University Press, ISBN 0-521-52923-9
- Pless, Vera (1998), Introduction to the Theory of Error-Correcting Codes (3rd ed.), Wiley Interscience, ISBN 0-471-19047-0
- Roman, Steven (1992), Coding and Information Theory, GTM, vol. 134, Springer-Verlag, ISBN 0-387-97812-7
- Welsh, Dominic (1988), Codes and Cryptography, Oxford University Press, ISBN 0-19-853287-3
Further reading
[edit]- MacWilliams, F.J.; Sloane, N.J.A. (1977), The Theory of Error-Correcting Codes, North-Holland, ISBN 0-444-85193-3