一种软判决下的本原BCH码盲识别方法
A Blind Recognition Method for Primitive BCH Codes in Soft Decision Situations

为解决现有BCH码识别方法容错性较差的问题,提出了一种软判决下的本原BCH码盲识别(SDBR)方法。首先,将截获数据进行解调软判决得到比特序列和对应可靠性信息,然后对比特序列进行码字划分,再由软判决可靠性信息建立码根可靠性系数,以此计算不同码根出现的概率,并引入Kullback？？Leibler散度来确定码长;其次,定义公共码根可靠性统计量并建立二元假设检验,在不同本原多项式下对公共码根进行判定;最后,利用公共码根连续分布特点识别本原多项式,进而由所有公共码根计算生成多项式。仿真结果表明:SDBR方法在信噪比大于7 dB时能有效对常用本原BCH码进行识别;与基于码根信息差熵的方法相比,容错性提升了1.8 dB。
A soft decision based blind recognition (SDBR) method for primitive BCH codes is proposed to solve the problem that existing recognition methods have low error？？resilient capabilities. Firstly, bit sequences as well as the corresponding reliability information are obtained by soft demodulation of the intercepted data, then code words are divided and a reliability coefficient of code roots is established with the reliability information to calculate the occurrence probability of code roots, and code length is estimated by using Kullback？？Leibler divergence. Secondly, reliability statistics of common code roots are defined and a binary hypothesis test is built, then common code roots are verified under different primitive polynomials. Finally, the right primitive polynomial is recognized by using the continuous distribution characteristics of common code roots, and a generator polynomial is calculated from all these code roots. Simulation results show that the SDBR method effectively recognizes the commonly used primitive BCH codes when the signal？？to？？noise ratio is above 7 dB. A comparison with the roots information dispersion entropy based method shows that the SDBR method improves the error？？resilient performance by 1.8 dB