| 摘要: |
| 在非合作通信的研究中,加扰编码码字的盲识别具有关键作用。现有的加扰编码码字盲识别研究主要集中在单一信道编码盲识别或扰码盲识别,这些方法在实际系统中往往不适用于加扰与编码的级联场景,且在误码情况下识别效率较低。为解决这一问题,本文提出了一种面向加扰卷积码级联场景的扰码与卷积码联合盲识别算法,该算法基于移位等效码字熵率。首先,本文利用卷积码字加扰后的性质构造移位等效码字,从而将扰码盲识别问题转化为等效卷积码判决问题。其次,由于使用传统算法判决移位等效码字过于复杂并且运算资源消耗过高,本文提出了一种基于信息熵率的卷积码快速判断方法,并推导出了算法实现所需的相关参数,实现了低复杂度和高效率的快速联合盲识别。通过仿真实验,我们证明了本文所提方法能有效地对加扰卷积码进行联合识别。在信道传输误比特率小于6%的情况下,扰码识别正确率达到了84.5%以上,扰码和卷积码的联合识别率超过了80%,展现了良好的抗噪能力。 |
| 关键词: 扰码 卷积码 联合盲识别 熵率 |
| DOI：10.19363/J.cnki.cn10-1380/tn.2023.08.08 |
| Received:January 06, 2021Revised:February 03, 2021 |
| 基金项目:本课题得到中国科学院C类战略性先导科技专项(No. XDC02040300)资助。 |
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| Blind Recognition of Scrambled Convolutional Code Based on Calculating Shift Equivalent Codeword Entropy Rate |
| WANG Zhongfang,HUANG Weiqing,ZHAI Liuqun,HU Keke,WEI Dong |
| School of Cyber Security, University of Chinese Academy of Sciences, Beijing 100093, China;Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100049, China;Department of Electronic Engineering, Tsinghua University, Beijing 100084, China |
| Abstract: |
| In the field of non-cooperative communication research, the blind identification of codewords that have undergone scrambling and encoding is of critical significance. Existing studies primarily concentrates on two aspects: the blind identification of individual channel-encoded codewords and the blind identification of scrambled codewords. These methods typically falter in complex scenarios where scrambling and encoding are concatenated, and they also suffer from reduced recognition efficiency in the presence of coding errors. To overcome this limitation, this paper introduces a novel algorithm that enables joint blind identification of both scrambling and convolution codes within concatenated configurations. The foundation of this algorithm lies in the entropy rate of shifted equivalent codewords. To begin with, we leverage the inherent characteristics of convolution codewords after scrambling to construct shifted equivalent codewords. This innovation transforms the challenge of scrambling blind identification into a more manageable problem of determining equivalent convolution codes. Traditional algorithms used for deciding on shifted equivalent codewords are known for their complexity and exorbitant consumption of computational resources. Acknowledging this obstacle, we propose a streamlined decision-making method specifically tailored for convolution codes, which is based on the information entropy rate. The relevant parameters required for the successful implementation of this algorithm are derived with precision, resulting in a solution characterized by both low computational complexity and high operational efficiency. Our simulation experiments provide compelling evidence for the effectiveness of the proposed method in the context of joint identification of scrambled convolution codes. In scenarios where the channel transmission bit error rate is maintained below 6%, our method achieved a scrambling recognition accuracy exceeding 84.5%, and a joint recognition rate for both scrambling and convolution codes that surpassed 80%. These results not only affirm the efficacy of our approach but also demonstrate its robust resistance to noise, underlining its potential applicability across a wide spectrum of non-cooperative communication systems. |
| Key words: scrambler convolutional code joint blind recognition entropy rate |
