CAJ | 학술논문

针对本原BCH码编码参数的盲识别问题，该文提出了一种基于概率逼近的盲识别方法。首先，利用Gauss分布和Poisson分布逼近随机码字的根概率特性，确定了搜索BCH码长的门限；然后，通过分析本原域元素的检错能力及同构对域的影响，应用临近域对的方法确定编码域，提高了其识别能力；最后，给出识别生成多项式时的共轭根系表，从而减少了计算量。仿真结果表明，在较高的误码率下，该方法能快速地识别出BCH码编码所采用的编码参数。
침대본원BCH마편마삼수적맹식별문제，해문제출료일충기우개솔핍근적맹식별방법。수선，이용Gauss분포화Poisson분포핍근수궤마자적근개솔특성，학정료수색BCH마장적문한；연후，통과분석본원역원소적검착능력급동구대역적영향，응용림근역대적방법학정편마역，제고료기식별능력；최후，급출식별생성다항식시적공액근계표，종이감소료계산량。방진결과표명，재교고적오마솔하，해방법능쾌속지식별출BCH마편마소채용적편마삼수。
To solve the issues of blind identification of primitive BCH codes encoding parameters, a novel identification algorithm with probability approximation is presented. Frist, by taking advantage of the approximation of random code words’ root probability character which uses Gaussian distribution and Poisson distribution, the thresholds for searching code length are structured. Second, though analyzing the checking ability of the primitive element and the impact of isomorphism on searching, the coding filed is determined by using the method of nearby fields pair which improves the performace of identification. Finally, the calculation is reduced by creating and using the conjugate roots table in the recognition of generator polynomial. Simulation results show that, the proposed algorithm achieves a significant improvement in identification probability even if in high BER situation.