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1. 海军航空大学信息融合研究所,山东 烟台 264001
2. 海军航空大学航空基础学院,山东 烟台 264001
3. 海军航空大学310教研室,山东 烟台 264001
[ "吴昭军(1992- ),男,四川遂宁人,海军航空大学博士生,主要研究方向为信道编码盲识别" ]
[ "张立民(1966- ),男,辽宁开原人,博士,海军航空大学教授,主要研究方向为卫星信号处理及应用" ]
[ "钟兆根(1984- ),男,江西南昌人,博士,海军航空大学讲师,主要研究方向为通信信号盲分离与统计信号处理" ]
[ "龙玉峰(1982- ),男,山东烟台人,海军航空大学博士生,主要研究方向为飞行器故障检测与诊断" ]
网络出版日期:2020-01,
纸质出版日期:2020-01-25
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吴昭军, 张立民, 钟兆根, 等. 基于平均余弦符合度下的本原BCH码盲识别[J]. 通信学报, 2020,41(1):15-24.
Zhaojun WU, Limin ZHANG, Zhaogen ZHONG, et al. Blind recognition of primitive BCH code based on average cosine conformity[J]. Journal on communications, 2020, 41(1): 15-24.
吴昭军, 张立民, 钟兆根, 等. 基于平均余弦符合度下的本原BCH码盲识别[J]. 通信学报, 2020,41(1):15-24. DOI: 10.11959/j.issn.1000-436x.2020022.
Zhaojun WU, Limin ZHANG, Zhaogen ZHONG, et al. Blind recognition of primitive BCH code based on average cosine conformity[J]. Journal on communications, 2020, 41(1): 15-24. DOI: 10.11959/j.issn.1000-436x.2020022.
为克服现有 BCH 码识别算法在低信噪比下适应性差的缺点,提出了一种基于平均余弦符合度的识别算法。首先遍历可能的码长值以及m级本原多项式域,进行初始码根校验匹配,从而完成码长识别;然后在识别出码长前提下,遍历m级本原多项式下的GF(2
)域,其最强纠错能力的本原多项式即为GF(2
)域生成多项式;最后求取所有连续码根最小多项式对应的最小公倍式,完成编码生成多项式识别。在校验匹配过程中,引入了平均余弦符合度统计量,基于软判决下符合度的统计特性以及最小错误判决准则求解出最优门限,从而实现本原BCH码参数快速识别。仿真结果表明,推导的符合度统计特性与实际情况一致,所提算法能在低信噪比下有效完成参数识别,同时具有较好的低信噪比适应能力,在信噪比为5 dB,码长为511的条件下,能够完成参数的可靠识别,与目前算法相比,所提算法性能优于现有的软判决算法,且比硬判决算法提升1~3.5 dB。
In order to overcome the poor performance of existing algorithms for recognition of BCH code in low signal-to-noise ratio (SNR)
a recognition algorithm based on average cosine conformity was proposed.Firstly
by traversing the possible values of code length and m-level primitive polynomial fields
the code l
ength was identified by matching the initial code roots.Secondly
on the premise of recognizing the code length
the GF(2
m
) domain was traversed under the m-level primitive polynomial and the primitive polynomial with the strongest error-correcting ability was the generator polynomial for the domain.Finally
the minimum common multiple corresponding to the minimum polynomial of code roots was obtained
and the BCH code generator polynomial was recognized.In checking matching
the statistic of average cosine conformity was introduced.The optimal threshold was solved based on the minimum error decision criterion and distribution of the statistic to realize the fast identification of the BCH.The simulation results show that the deduced statistical characteristics are consistent with the actual situation
and the proposed algorithm can achieve reliable recognition under SNR of 5 dB and code length of 511.Comparing with existing algorithms
the performance of the proposed algorithm is better than that of the existing soft-decision algorithm and 1~3.5 dB better than that of the hard-decision algorithms.
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