A Novel Method for Blind Identification of a (n, n-1, m) Convolutional Code

The existing methods for identification of a ( , , ) 1 n n m convolutional code are not applicable in the cases of high bit error rates or need a large amount of computation. To overcome the limitations, a novel blind identification method is proposed. First, based on the parity check equation set, the parity check vector of a convolutional code is estimated by using the proposed recursive algorithm. Second, due to the orthogonality between the parity check matrix and the generator matrix, a set of polynomial generator bases are obtained. Finally, the canonical generator matrix is reconstructed by using the polynomial generator bases. Experimental results show the method is effective. The method has high robustness to bit errors. It does not need to search for the parity check vector exhaustively, and therefore its computational complexity is much lower than that of the existing method.