本文選題：信道編碼技術(shù)　切入點(diǎn)：線性分組碼　出處：《河北大學(xué)》2017年碩士論文　論文類(lèi)型：學(xué)位論文

【摘要】：在數(shù)字通信系統(tǒng)中,為了抗擊信息在傳輸過(guò)程中受到的影響和干擾,提高信息傳輸?shù)目煽啃?信道編碼技術(shù)得到迅速發(fā)展。由于信道編碼技術(shù)應(yīng)用范圍日益增大,信道編碼盲識(shí)別技術(shù)應(yīng)運(yùn)而生。其目的是在僅有少量甚至沒(méi)有任何先驗(yàn)信息的前提下識(shí)別出截獲碼流的編碼體制和相關(guān)參數(shù),從而恢復(fù)出原始信息序列。它在信息對(duì)抗、通信偵測(cè)以及智能通信等領(lǐng)域具有重要的研究?jī)r(jià)值。本文重點(diǎn)研究了二進(jìn)制線性分組碼參數(shù)的全盲識(shí)別問(wèn)題,論文的主要工作如下:(1)介紹了線性分組碼的理論知識(shí)、盲識(shí)別的數(shù)學(xué)模型和識(shí)別參數(shù),為后面章節(jié)線性分組碼的全盲識(shí)別算法研究奠定了基礎(chǔ),并指出線性分組碼是本文的研究對(duì)象。(2)針對(duì)線性分組碼參數(shù)盲識(shí)別容錯(cuò)性能差、復(fù)雜度高和半盲識(shí)別的問(wèn)題,提出了一種基于特征融合的線性分組碼全盲識(shí)別算法。首先根據(jù)實(shí)際序列與隨機(jī)序列碼重分布概率間較大的差異性,研究了一種運(yùn)用碼重標(biāo)準(zhǔn)差率差值、碼重信息熵分別同時(shí)識(shí)別碼長(zhǎng)和起始點(diǎn)的算法;然后比較這兩種特征參數(shù)識(shí)別效果又進(jìn)一步改進(jìn),提出了一種新的融合特征參數(shù)來(lái)同時(shí)識(shí)別碼長(zhǎng)和起始點(diǎn)的算法;最后通過(guò)建立矩陣進(jìn)行模二化簡(jiǎn)求解生成矩陣,完成線性分組碼參數(shù)的全盲識(shí)別。通過(guò)理論分析和仿真驗(yàn)證,該算法簡(jiǎn)單易行且復(fù)雜度低,在誤碼率為0.025的條件下對(duì)中短碼的全盲識(shí)別率高達(dá)90%,誤碼率為0.005的條件下對(duì)中長(zhǎng)碼的全盲識(shí)別率達(dá)到80%。(3)針對(duì)高誤碼率條件下高碼率循環(huán)碼參數(shù)的全盲識(shí)別問(wèn)題,提出了一種基于最大公因式階數(shù)相異度的循環(huán)碼全盲識(shí)別算法。首先根據(jù)循環(huán)移位前后碼字的最大公約式階數(shù),利用實(shí)際序列與隨機(jī)序列階數(shù)分布概率間的差異性,提出了一種基于數(shù)據(jù)挖掘中相異性度量函數(shù)同時(shí)識(shí)別起始點(diǎn)和碼長(zhǎng)的算法;然后根據(jù)循環(huán)碼特性,計(jì)算階數(shù)分布差值來(lái)識(shí)別生成多項(xiàng)式,實(shí)現(xiàn)了循環(huán)碼參數(shù)的全盲識(shí)別。該算法簡(jiǎn)單易行且容錯(cuò)性較強(qiáng),在誤碼率為0.013的條件下對(duì)中長(zhǎng)碼的全盲識(shí)別效果較好。
[Abstract]:In digital communication system, in order to resist the influence and interference of information transmission and improve the reliability of information transmission, channel coding technology has been developed rapidly. The blind identification technique of channel coding arises at the historic moment. Its purpose is to recognize the coding system and related parameters of the intercepted bitstream without even any prior information, so as to recover the original information sequence. Communication detection and intelligent communication have important research value. This paper focuses on the whole blind identification of binary linear block code parameters. The main work of this paper is as follows: 1) the theoretical knowledge of linear block code is introduced. The mathematical model and identification parameters of blind block code are the foundation of the whole blind recognition algorithm of linear block code in the following chapters. It is pointed out that linear block code is the research object of this paper. (2) for the parameter blind recognition of linear block code, the fault-tolerant performance of linear block code is poor. In order to solve the problem of high complexity and semi-blind recognition, this paper proposes a full blind recognition algorithm for linear block codes based on feature fusion. Firstly, according to the large differences between the distribution probability of code weight distribution between real sequences and random sequences, In this paper, an algorithm using the difference of code weight standard deviation rate and the code weight information entropy to identify the code length and the starting point respectively is studied, and the recognition effect of these two characteristic parameters is further improved. This paper presents a new algorithm to identify the length of code and the starting point at the same time by combining the characteristic parameters. Finally, by establishing the matrix to solve the generation matrix by module reduction, the full blind identification of the parameters of the linear block codes is accomplished, which is verified by theoretical analysis and simulation. The algorithm is simple and easy to implement and has low complexity. Under the condition that the BER is 0.025, the full blind recognition rate of medium and short codes is as high as 90 and that of medium and long codes is up to 80 and 80 under the condition of BER 0.005.) for the problem of full blind recognition of cyclic code parameters at high bit error rate, In this paper, a full blind recognition algorithm for cyclic codes based on the order dissimilarity of the largest common factor is proposed. Firstly, according to the maximum convention order of the code word before and after cyclic shift, the difference between the distribution probability of the order of the real sequence and the random sequence is used. In this paper, an algorithm based on the heterogeneity measure function in data mining is proposed to identify both the starting point and code length, and then, according to the characteristics of cyclic code, the order distribution difference is calculated to identify the generating polynomial. The algorithm is simple and fault-tolerant, and has a good effect on the full blind recognition of medium and long code under the condition of error rate of 0.013.
【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】：2017
【分類(lèi)號(hào)】：TN911.22

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