Convolutional code length blind recognition method based on Gaussian column elimination

Abstract

The invention belongs to the technical field of code word recognition in a wireless communication system, and particularly relates to a Gaussian column elimination convolutional code length blind recognition method. According to the method disclosed by the invention, whether a linear correlation column exists in a storage matrix or not is searched through matrix column transformation of elementary transformation carried out in a Gaussian elimination process according to the correlation between code elements of a coding sequence; according to the characteristic that a column where a check bit is located can be fully converted into '0' under the condition of no error code, cosine similarity is introduced, and parameters of a convolutional code are determined by measuring fluctuation of the cosine similarity of a normalized column weight vector of the proportion of '1' in each column after Gaussian column elimination of a codeword matrix of the convolutional code and a normalized column weight vector of a random binary matrix. According to the method, 90% code length recognition probability can be achieved when the bit error rate is 0.01, the application range is wide, and the method has good recognition performance for the code lengths of convolutional codes with different code lengths, different code rates and different constraint degrees.

Description

technical field [0001] The invention belongs to the technical field of blind recognition of channel coding in a wireless communication system, and in particular relates to a blind recognition method of a code length of a convolutional code based on Gaussian elimination. Background technique [0002] At present, during channel transmission of digital signals, the signal will be distorted due to noise interference. In order to improve the reliability of data transmission, it is necessary to perform channel coding on the signal. Channel coding includes scrambling, error correction coding and interleaving. Convolutional codes belong to the most important class of codes in error correction coding. As a block code, convolutional codes have the characteristics of short code length, correlation between code words, simple encoding and decoding methods, and good error correction performance. Therefore, it is widely used in satellite communication, deep space communication, mobile com...

AI Technical Summary

Problems solved by technology

This method has a relatively small amount of calculation, but it is only for the recognition of 1 / 2 code rate convolutional codes, and the recognition can only be completed when the starting position of the codeword is known.

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