A Blind Identification Method of Self-synchronous Scramblers Based on Optimization of Established Cost Function

HAN Shunan; ZHANG Min; LI Xinhao

doi:10.11999/JEIT171026

Volume 40 Issue 8

Aug. 2018

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Article Navigation > Journal of Electronics & Information Technology > 2018 > 40(8): 1971-1977

HAN Shunan, ZHANG Min, LI Xinhao. A Blind Identification Method of Self-synchronous Scramblers Based on Optimization of Established Cost Function[J]. Journal of Electronics & Information Technology, 2018, 40(8): 1971-1977. doi: 10.11999/JEIT171026

Citation:

HAN Shunan, ZHANG Min, LI Xinhao. A Blind Identification Method of Self-synchronous Scramblers Based on Optimization of Established Cost Function[J]. Journal of Electronics & Information Technology, 2018, 40(8): 1971-1977. doi: 10.11999/JEIT171026

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A Blind Identification Method of Self-synchronous Scramblers Based on Optimization of Established Cost Function

doi: 10.11999/JEIT171026

HAN Shunan^{*张旻李歆昊},
ZHANG Min,
LI Xinhao

Funds:

The National Natural Science Foundation of China (61602491)

Received Date: 2017-11-02
Rev Recd Date: 2018-03-23
Publish Date: 2018-08-19

Abstract

Abstract

Since the probability bias between 0 and 1 bit in a convolutional code sequence is very small, the existing method based on the probability bias in the input sequence is ineffective for the identification of a self-synchronous scrambler placed after a convolutional encoder. To solve this problem, a novel method for the blind identification of a self-synchronous scrambler is proposed. First, the scrambled convolutional code sequence is divided into blocks, and a new bit sequence is generated, in which each bit is the dot product of a scrambled bit block with a parity check vector of the convolutional code. Second, based on the criteria of maximizing the probability that the linear equations in the generated bits hold, the cost function of the feedback polynomial coefficients of the self-synchronous scrambler is established using the soft decision sequence, which is the output of the demodulator. Third, according to the characteristic of the number of terms in the feedback polynomial, the dynamic fireworks algorithm is modified by constraining the values of elements in fireworks, and the cost function is optimized using the modified dynamic fireworks algorithm. Simulation experiments show the effectiveness of the proposed algorithm. There is no need to search for the feedback polynomial exhaustively in the proposed algorithm. It is robust to the noise and the number of data required is small. Moreover, along with the increase of the number of received data or the decrease of the order of the feedback polynomial, the correct identification ratio of the proposed method increases.
- Self-synchronous scrambler,
- Convolutional code,
- Feedback polynomial,
- Parity check vector,
- Fireworks algorithm

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References(24)

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