摘要
针对目前RSC码盲识别算法容错性不好、计算量大的缺点,提出了基于离散PSO算法的RSC码识别方法.首先根据RSC码特殊的编码结构,构建出基于离散PSO算法的识别模型,并推导出了算法的适应度函数以及算法终止的判决门限;其次,按照构建出的识别模型,提出了详细的RSC码编码参数的识别步骤和流程框图,克服了目前RSC码识别算法的缺陷.仿真实验表明:该算法在寄存器个数较小时,具有较高的识别性能;同时在误码率高达0.05条件下,各种寄存器个数下的RSC码参数识别率均能达到90%以上,部分甚至达到100%,且算法的计算量仅仅与寄存器个数以及码元路数呈线性增加,与Walsh-Hadamard算法相比,计算量大大减少.
In order to address the defects of poor error tolerance and large amount of calculation in current RSC encoder recognition algorithms,a newalgorithm based on discrete PSO is proposed. Firstly,because of the special structure of RSC codes,the recognized model based on the discrete PSO algorithm is built and the fitness of algorithm as well as terminal threshold are deduced. Then,the detailed steps and process to recognize the RSC codes are put forward according to the identification model to overcome the defects in current algorithms. The simulation results showthat the algorithm has perfect performance when the number of memories is small. The correct ratio of recognition can reach 90% at different numbers of memories when the rate of bit error is 0. 05,some of which can even reach 100%. Besides,the calculation of algorithm increases linearly with the number of memories and branches of codes,which is reduced greatly compared with the WalshHadamard.
作者
吴昭军
张立民
钟兆根
刘杰
WU Zhao-jun;ZHANG Li-min;ZHONG Zhao-gen;LIU Jie(Department of Electronics and Information Engineering,Naval Aviation University,Yantai,Shandong 264001,China;Department of Information Fusion,Naval Aviation University,Yantai,Shandong 264001,China)
出处
《电子学报》
EI
CAS
CSCD
北大核心
2018年第7期1644-1651,共8页
Acta Electronica Sinica
基金
国家自然科学基金重大研究计划(No.91538201)
泰山学者工程专项经费(No.Ts201511020)
关键词
RSC码
离散PSO算法
适应度函数
终止门限
识别
recursive systematic convolutional codes
the discrete particle swarm optimization
the function of fitness
terminal threshold
recognition
