Open AccessA Blind Recognition Algorithm of Scrambler after Convolutional Encoder
Author(s) -
Zhongfang Wang,
Liuqun Zhai,
Jiao Fu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1944/1/012010
Subject(s) - scrambling , computer science , encoder , algorithm , encoding (memory) , convolutional code , speech recognition , channel (broadcasting) , artificial intelligence , decoding methods , telecommunications , operating system
In a wireless communication system, the data is usually scrambled after channel encoding. However, existing research on blind recognition often ignores the pseudo-random scrambling of channel encoding data, which is not in line with the actual situation. To solve this problem, this paper proposes an algorithm to recognize the scrambler parameters with convolutional codes. First, we transform this problem into a cognition problem of cancelling scrambling sequence by using the properties of the polynomial of scrambler. Then, we put forward a fast judgment method after the cancellation of scrambling. The proposed method is based on the conditional entropy and can effectively identify the scrambler after the convolutional encoder. The method has a better performance of resisting error comparing to the traditional method and saves computing resources. Simulation results show that the parameters of the scrambler can still be determined effectively when the bit error rate is 6% in the case of sufficient data.