The optimal and suboptimal structured algorithms of linear block codes from the geometrical perspective are represented.The minimum distance and weight property lemmas and the theorem are proved for the generator matr...The optimal and suboptimal structured algorithms of linear block codes from the geometrical perspective are represented.The minimum distance and weight property lemmas and the theorem are proved for the generator matrix.Based upon the property of generator matrix,the structured algorithms of linear block codes are demonstrated.Since the complexity of optimal structured algorithm is very high,the binary linear block codes is searched by using the suboptimal structured algorithm.The comparison with Bose-Chaudhuri-Hocquenqhem（BCH） codes shows that the searched linear block codes are equivalent on minimum distance and can be designed for more block lengths.Because the linear block codes are used widely in communication systems and digital applications,the optimal and suboptimal structured algorithms must have great future being widely used in many applications and perspectives.展开更多
This study proposes a novel multi-fractal spectrumbasedapproach to distinguish linear block codes from its selfsynchronousscrambled codes. Given that the linear block codeand self-synchronous scrambled linear block co...This study proposes a novel multi-fractal spectrumbasedapproach to distinguish linear block codes from its selfsynchronousscrambled codes. Given that the linear block codeand self-synchronous scrambled linear block code share the propertyof linear correlation, the existing linear correlation-basedidentification method is invalid for this case. This drawback can becircumvented by introducing a novel multi-fractal spectrum-basedmethod. Simulation results show that the new method has highrobustness and under the same conditions of bit error, the lowerthe code rate, the higher the recognition rate. Thus, the methodhas significant potential for future application in engineering.展开更多
针对非合作信号处理中的线性分组码盲识别问题,提出了一种基于有限域傅里叶变换(Galois field Fourier transform,GFFT)的检测识别方法。该方法对接收码序列按不同长度进行分段,对分段码字进行有限域上的傅里叶变换并计算其频谱的累积...针对非合作信号处理中的线性分组码盲识别问题,提出了一种基于有限域傅里叶变换(Galois field Fourier transform,GFFT)的检测识别方法。该方法对接收码序列按不同长度进行分段,对分段码字进行有限域上的傅里叶变换并计算其频谱的累积量。通过频谱累积量的不同分布情况,可以估计出正确的分组码长度。同时从频谱累积量中找出码字生成多项式的根,进而得到码字的生成多项式。仿真实验验证了算法的有效性,并对算法的误码适应能力和计算复杂度进行了仿真分析,最后给出了在不同误码环境下最优的频谱累积次数。展开更多
文摘The optimal and suboptimal structured algorithms of linear block codes from the geometrical perspective are represented.The minimum distance and weight property lemmas and the theorem are proved for the generator matrix.Based upon the property of generator matrix,the structured algorithms of linear block codes are demonstrated.Since the complexity of optimal structured algorithm is very high,the binary linear block codes is searched by using the suboptimal structured algorithm.The comparison with Bose-Chaudhuri-Hocquenqhem（BCH） codes shows that the searched linear block codes are equivalent on minimum distance and can be designed for more block lengths.Because the linear block codes are used widely in communication systems and digital applications,the optimal and suboptimal structured algorithms must have great future being widely used in many applications and perspectives.
基金supported by the National Natural Science Foundation of China(61171170) the Natural Science Foundation of Anhui Province(1408085QF115)
文摘This study proposes a novel multi-fractal spectrumbasedapproach to distinguish linear block codes from its selfsynchronousscrambled codes. Given that the linear block codeand self-synchronous scrambled linear block code share the propertyof linear correlation, the existing linear correlation-basedidentification method is invalid for this case. This drawback can becircumvented by introducing a novel multi-fractal spectrum-basedmethod. Simulation results show that the new method has highrobustness and under the same conditions of bit error, the lowerthe code rate, the higher the recognition rate. Thus, the methodhas significant potential for future application in engineering.
文摘针对非合作信号处理中的线性分组码盲识别问题,提出了一种基于有限域傅里叶变换(Galois field Fourier transform,GFFT)的检测识别方法。该方法对接收码序列按不同长度进行分段,对分段码字进行有限域上的傅里叶变换并计算其频谱的累积量。通过频谱累积量的不同分布情况,可以估计出正确的分组码长度。同时从频谱累积量中找出码字生成多项式的根,进而得到码字的生成多项式。仿真实验验证了算法的有效性,并对算法的误码适应能力和计算复杂度进行了仿真分析,最后给出了在不同误码环境下最优的频谱累积次数。
