基于余弦符合度的自同步扰码盲识别

张立民; 谭继远; 钟兆根; 吴昭军

doi:10.11999/JEIT210248

基于余弦符合度的自同步扰码盲识别

doi: 10.11999/JEIT210248

1.
海军航空大学信息融合研究所烟台 264001
2.
海军航空大学航空基础学院烟台 264001
3.
西南电子电信研究所成都 610000

基金项目: 国家自然科学基金(91538201)；泰山学者工程专项(ts201511020)；信息系统安全技术重点实验室基金(6142111190404)

详细信息

作者简介:
张立民：男，1966年生，教授，博士生导师，研究方向为卫星信号处理及应用

谭继远：男，1994年生，博士生，研究方向为信道编码识别

钟兆根：男，1984年生，博士，副教授，研究方向为扩频信号处理

吴昭军：男，1992年生，博士，助理研究员，研究方向为信道编码识别

通讯作者:
谭继远　tjiyuan@outlook.com

中图分类号: TN911.7
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- 被引次数: 0
出版历程
- 收稿日期: 2021-03-26
- 修回日期: 2021-06-29
- 网络出版日期: 2021-07-08
- 刊出日期: 2022-04-18

Blind Recognition of Self-synchronous Scramblers Based on Cosine Conformity

1.
Department of Information Fusion, Naval Aviation University, Yantai 264001, China
2.
School of Aviation Basis, Naval Aviation University, Yantai 264001, China
3.
Southwest Electronics and Telecommunications Research Institute, Chengdu 610000, China

Funds: The National Natural Science Foundation of China (91538201), Taishan Scholar Special Foundation (ts201511020), The Chinese National Key Laboratory of Science and Technology on Information System Security (6142111190404)

摘要

摘要: 为克服现有非合作自同步扰码识别算法在低信噪比下识别率低、适应性差的缺点，该文提出一种基于余弦符合度的自同步扰码盲识别方法。首先基于信源不平衡性和自同步扰码解扰原理建立自同步扰码的含错校验方程，然后将接收到的软判决序列转化为信息码元的后验概率序列，遍历可能的生成多项式，在遍历的过程中引入余弦符合度作为统计量，通过分析符合度的统计特性求解出最优的判别门限，根据统计量和判别门限的关系完成自同步扰码生成多项式的识别。仿真结果表明：该算法能有效识别出生成多项式，且在低信噪比下识别率优于现有算法，具有较好的低信噪比适应能力，在信源不平衡度ε为0.1，截获扰码序列长度为800 bit和ε为0.05，截获扰码序列长度为3000 bit时，能够有效完成生成多项式的识别，与目前算法相比，该文算法识别性能优于现有的硬判决算法，且比硬判决算法性能提升1～2 dB。
- 自同步扰码 /
- 余弦符合度 /
- 信源不平衡度 /
- 低信噪比
Abstract: In order to overcome the shortcomings of the existing non-cooperative self-synchronous scramblers recognition algorithms with low recognition rate and poor adaptability under low signal-to-noise ratio, a blind recognition method of self-synchronous scramblers based on cosine conformity is proposed. Firstly, based on the source imbalance and self-synchronous scramblers descrambling principle, the error-containing check equation of the self-synchronous scramblers is established, and then the received soft decision sequence is converted into the posterior probability sequence of the information symbol. The possible generating polynomials are traversed. The cosine conformity is introduced as a statistic in the traversal process, and the optimal discrimination threshold is solved by analyzing the statistical characteristics of the cosine conformity. The self-synchronous scramblers generating polynomial is identified according to the relationship between the statistics and the discrimination threshold. The simulation results show that the algorithm can effectively identify the generating polynomial, and the recognition rate is better than the existing algorithm under low signal-to-noise ratio, and it has good low signal-to-noise ratio adaptability. When the source imbalance is 0.1, the length of the intercepted scrambling code sequence is 800 bit and 0.05, and the length of the intercepted scrambling code sequence is 3000 bit, the identification of the generating polynomial can be effectively completed. Compared with the current algorithm, the recognition performance of this algorithm is better than the existing hard decision. The performance of the algorithm is improved by 1～2 dB compared with the hard decision algorithm.
- Self-synchronous scramblers /
- Cosine conformity /
- Source imbalance /
- Low signal-to-noise ratio

HTML全文

图 1 自同步扰码加扰器结构

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图 2 自同步扰码解扰

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图 3 自同步扰码模型

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图 4 统计量和判别门限关系图

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图 5 截获扰码序列长度对算法识别率的影响

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图 6 生成多项式阶数对算法识别率的影响

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图 7 信源不平衡度对算法识别率的影响

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图 8 4种算法的容错性能对比

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