A Method for Blind Identification of a Scrambler Based on Matrix Analysis
Shunan Han, Min Zhang · IEEE Communications Letters · 2018
Existing methods for identifying a scrambler placed after a convolutional encoder require prior knowledge about the encoding type and a dual word of the convolutional code. To overcome these limitations, we propose here a method for blind identification of a scrambler based on matrix analysis. The rank behaviors of self-synchronously and synchronously scrambled convolutional code bit matrices are first analyzed theoretically. Based on their rank deficient characteristics, preliminary identification of the encoding type of a received sequence can then take place. After this, by using the bases in the null space of the received bit matrix, the feedback polynomial of the scrambler can be reconstructed. Furthermore, according to the rank behavior of the descrambled sequence, the type of the scrambler can be determined. This method can thus arrive at the blind identification of a scrambler without any prior knowledge.