Channel coding technology is widely used in digital wireless communication systems for forward error correction. Channel coding recognition means to reversely recognizing the coding parameters. For blind recognition of convolutional interleavers

the existing method based on the existence of frame sync codes has high computational complexity

and is not able to recognize the depth starting point. The method even fails for certain interleaver and frame length combinations. Its main computation is in recognizing the period of frame sync code in the interleaved sequence. In this paper

a low complexity method which avoids lots of repeated computation is developed for the period recognition. Then

a method called cyclic convolutional de-interleaving is proposed to de-interleave the partitioned-and-summed version of the interleaved sequence

and thus the frame sync code and the interleaver parameters are recovered in the meantime. The proposed methods are able to recognize the whole parameters for any interleaver and frame length combinations. Theoretical and simulation results show that

compared to the existing method

the proposed methods reduce the computational complexity by a percentage ranging from around 50% to more than 90%

and improves robustness against channel noise by more than 2dB

showing high application value in areas like cognitive radio.