本文關(guān)鍵詞： 信道編碼 線性分組碼 循環(huán)碼 BCH碼 盲識(shí)別　出處：《河北大學(xué)》2015年碩士論文　論文類型：學(xué)位論文

【摘要】：為保證實(shí)際數(shù)字通信系統(tǒng)中信息傳輸?shù)目煽啃院桶踩?通常使用信道編碼技術(shù),該技術(shù)在許多領(lǐng)域得到飛速發(fā)展,隨之信道編碼識(shí)別技術(shù)也開始備受關(guān)注。信道編碼識(shí)別的目的是僅根據(jù)截獲數(shù)據(jù)序列,在僅有少量甚至無任何先驗(yàn)信息的條件下識(shí)別出截獲數(shù)據(jù)流的編碼體制和參數(shù),從而提取原始信息序列。而線性分組碼編碼簡單、糾錯(cuò)能力較強(qiáng),應(yīng)用于數(shù)字通信的許多領(lǐng)域中。因此本文主要針對二進(jìn)制線性分組碼參數(shù)的盲識(shí)別問題展開研究。首先簡要介紹了分組碼知識(shí)及編碼識(shí)別的數(shù)學(xué)模型和識(shí)別參數(shù),為下面章節(jié)參數(shù)盲識(shí)別算法的討論奠定理論基礎(chǔ)。接著總結(jié)現(xiàn)有線性分組碼參數(shù)識(shí)別算法的優(yōu)缺點(diǎn),進(jìn)而提出一種利用碼重相似度的算法識(shí)別碼長、同步點(diǎn),這是根據(jù)實(shí)際序列與隨機(jī)序列的碼重分布之間的差異最大特性來識(shí)別的,并利用僅在數(shù)學(xué)理論證明中出現(xiàn)的特征——深度分布,識(shí)別生成矩陣,從而完成對分組碼的盲識(shí)別。碼重相似度的算法理論過程簡單易懂,仿真結(jié)果表明該算法在誤碼率0.01下能有效識(shí)別。最后針對分組碼的特殊碼字——循環(huán)碼進(jìn)行研究:對于BCH碼的半盲識(shí)別問題,根據(jù)其循環(huán)性,利用輾轉(zhuǎn)相除法求得移位前后碼字的最高公因式,其階數(shù)相對于隨機(jī)序列來說分布極不平衡,根據(jù)此差異性,提出一種運(yùn)用方差差值、平均歐式距離的量化指標(biāo)分別識(shí)別碼長的算法,比較這兩種量化指標(biāo)識(shí)別效果,進(jìn)而提出一種新的融合指標(biāo)識(shí)別碼長的算法,并構(gòu)建公因式系數(shù)概率分布,識(shí)別生成多項(xiàng)式,實(shí)現(xiàn)了BCH碼的半盲識(shí)別。經(jīng)實(shí)驗(yàn)仿真,融合指標(biāo)識(shí)別碼長的算法容錯(cuò)性較好。為有效解決高誤碼率下高碼率循環(huán)碼的全盲識(shí)別問題,在BCH碼識(shí)別算法的啟發(fā)下,仍利用最高公因式階數(shù)分布之間的差異性特征,通過理論改進(jìn)和實(shí)驗(yàn)仿真,提出基于標(biāo)準(zhǔn)差率差值的最高公因式階數(shù)的循環(huán)碼全盲識(shí)別算法,該算法計(jì)算量較少,容錯(cuò)性強(qiáng),且在0.023的誤碼率下,對中短碼識(shí)別效果明顯。
[Abstract]:In order to ensure the reliability and security of information transmission in practical digital communication systems, channel coding technology is usually used, which has been developed rapidly in many fields. The purpose of channel coding recognition is to identify the encoding system and parameters of intercepted data streams only according to intercepted data sequences and without any prior information. In order to extract the original information sequence, the linear block code is easy to encode and has strong error correction ability. In this paper, the blind recognition of binary linear block code parameters is studied. Firstly, the mathematical model and identification parameters of block code knowledge and coding recognition are briefly introduced. It lays a theoretical foundation for the discussion of parameter blind identification algorithm in the following chapters. Then it summarizes the advantages and disadvantages of the existing linear block code parameter identification algorithms, and then proposes an algorithm based on the similarity of code weight to identify the length of code and the synchronization point. This is based on the maximum characteristic of the difference between the code weight distribution of the real sequence and the random sequence, and the generation matrix is identified by using the feature-depth distribution, which appears only in the mathematical theory proof. Thus the blind recognition of block codes is completed. The algorithm of code weight similarity is simple and easy to understand. Simulation results show that the algorithm can be recognized effectively under BER 0.01. Finally, the special codeword cyclic code of block code is studied. For semi-blind identification of BCH code, according to its circularity, The highest common factor of the code word before and after the shift is obtained by the method of tossing and rotating phase division, the order of which is extremely unbalanced relative to the random sequence. According to the difference, a difference of variance is proposed. The average Euclidean distance quantization index respectively identifies the code length algorithm, compares these two quantization index recognition effect, then proposes a new fusion index identification code length algorithm, and constructs the common factor coefficient probability distribution, recognizes the generation polynomial, The semi-blind recognition of BCH code is realized. The experiment results show that the algorithm of fusion index identification code length is fault-tolerant. In order to effectively solve the problem of full blind recognition of cyclic code with high bit error rate, the algorithm is inspired by BCH code recognition algorithm. Based on the difference between the order distribution of the highest common factor, and through theoretical improvement and experimental simulation, a full blind identification algorithm for cyclic codes based on the highest common factor order of standard deviation rate difference is proposed. The algorithm has less computation and strong fault tolerance. At the error rate of 0.023, the recognition effect of medium and short code is obvious.
【學(xué)位授予單位】：河北大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TN911.22

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