基于概率計(jì)算的極化碼譯碼研究
發(fā)布時(shí)間：2019-04-01 14:57
【摘要】：近些年提出的全新信道編碼解決方案極化碼,其相比其他現(xiàn)有的信道編碼方法具有最優(yōu)的理論性能以及較低的譯碼復(fù)雜度等優(yōu)勢(shì),并引起需要研究人員的注意。極化碼可以采用串行抵消算法或者置信傳播算法進(jìn)行譯碼,該算法在譯碼過(guò)程中為串行譯碼方式,這種譯碼特點(diǎn)結(jié)構(gòu)簡(jiǎn)單、復(fù)雜度較低,但是會(huì)存在較大的譯碼延遲問(wèn)題�；诟怕释评淼闹眯艂鞑ニ惴ㄊ菢O化碼譯碼算法中的一種,極化碼可以看作是一種基于圖模型的編碼方法,這個(gè)圖模型中的相鄰節(jié)點(diǎn)之間會(huì)存在概率上的依賴關(guān)系,所以可以使用置信傳播的方法完成圖中節(jié)點(diǎn)的概率推理以及更新過(guò)程,而且這種算法本身的并行運(yùn)算特點(diǎn)也能夠有效的減小延遲問(wèn)題。本文主要研究了基于概率計(jì)算的極化碼置信傳播譯碼算法。首先回顧了信道編碼的發(fā)展歷史和有關(guān)內(nèi)容,并介紹了提出極化碼的背景和有關(guān)的基本知識(shí)。極化碼是一種基于信道極化現(xiàn)象的編碼方案,并且是已經(jīng)被證明了能夠達(dá)到信道容量的唯一編碼方法。然后介紹了極化碼的串行抵消譯碼算法,該算法有結(jié)構(gòu)簡(jiǎn)單,復(fù)雜度低的特點(diǎn),之后介紹了能夠應(yīng)用在極化碼譯碼中的置信傳播算法,基于圖模型的置信傳播算法具有并行結(jié)構(gòu),并且其相對(duì)于串行抵消算法具有更短時(shí)延和更高的吞吐量,深入研究該算法具有重要的實(shí)用價(jià)值。不過(guò)該算法中涉及到的一些計(jì)算較為復(fù)雜,而概率計(jì)算的方法能夠降低原有算法的復(fù)雜度,所以本文對(duì)原有算法進(jìn)行了概率化并進(jìn)行了一系列優(yōu)化處理,通過(guò)仿真結(jié)果可以得出經(jīng)過(guò)優(yōu)化之后的概率計(jì)算方法能夠?qū)崿F(xiàn)與傳統(tǒng)算法相近的性能。最后基于分段方法的高精度概率計(jì)算方法被用來(lái)解決傳統(tǒng)概率計(jì)算中隨機(jī)序列較長(zhǎng)的問(wèn)題,該方法能夠在保證運(yùn)算精度的情況下縮短概率序列長(zhǎng)度,仿真結(jié)果表明在保證譯碼性能的前提下,這種方法能夠減少隨機(jī)序列長(zhǎng)度。
[Abstract]:Compared with other existing channel coding methods, polarization code, a new channel coding solution proposed in recent years, has the advantages of optimal theoretical performance and low decoding complexity, which requires the attention of researchers. Polarization codes can be decoded by serial cancellation algorithm or confidence propagation algorithm, which is a serial decoding mode in the decoding process. This decoding method is simple in structure and low in complexity, but there is a large decoding delay problem. The confidence propagation algorithm based on probabilistic reasoning is one of the decoding algorithms of polarization codes. Polarization codes can be regarded as a coding method based on graph model, and there will be probability dependence between adjacent nodes in this graph model. Therefore, confidence propagation can be used to complete the probabilistic reasoning and updating process of nodes in the graph, and the parallel operation characteristics of this algorithm can also effectively reduce the delay problem. This paper mainly studies the confidence propagation decoding algorithm of polarization codes based on probability calculation. Firstly, the development history and related contents of channel coding are reviewed, and the background and basic knowledge of polarizing codes are introduced. Polarization code is a kind of coding scheme based on channel polarization phenomenon, and it has been proved to be the only coding method that can reach the channel capacity. Then the serial cancellation decoding algorithm of polarization codes is introduced. The algorithm has the characteristics of simple structure and low complexity. Then it introduces the confidence propagation algorithm which can be used in the decoding of polarizing codes. The confidence propagation algorithm based on graph model has parallel structure, and it has shorter delay and higher throughput than the serial cancellation algorithm. It has important practical value to study this algorithm in depth. However, some of the computation involved in this algorithm is more complex, and the method of probability calculation can reduce the complexity of the original algorithm, so this paper has carried on the probability of the original algorithm and carried on a series of optimization processing, and the method of probability calculation can reduce the complexity of the original algorithm. The simulation results show that the optimized probability calculation method can achieve the same performance as the traditional algorithm. Finally, the high-precision probability calculation method based on piecewise method is used to solve the problem of long random sequence in traditional probability calculation. This method can shorten the length of probability sequence under the condition of ensuring the precision of operation. Simulation results show that this method can reduce the length of random sequences under the premise of ensuring decoding performance.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN911.22
本文編號(hào)：2451653
[Abstract]:Compared with other existing channel coding methods, polarization code, a new channel coding solution proposed in recent years, has the advantages of optimal theoretical performance and low decoding complexity, which requires the attention of researchers. Polarization codes can be decoded by serial cancellation algorithm or confidence propagation algorithm, which is a serial decoding mode in the decoding process. This decoding method is simple in structure and low in complexity, but there is a large decoding delay problem. The confidence propagation algorithm based on probabilistic reasoning is one of the decoding algorithms of polarization codes. Polarization codes can be regarded as a coding method based on graph model, and there will be probability dependence between adjacent nodes in this graph model. Therefore, confidence propagation can be used to complete the probabilistic reasoning and updating process of nodes in the graph, and the parallel operation characteristics of this algorithm can also effectively reduce the delay problem. This paper mainly studies the confidence propagation decoding algorithm of polarization codes based on probability calculation. Firstly, the development history and related contents of channel coding are reviewed, and the background and basic knowledge of polarizing codes are introduced. Polarization code is a kind of coding scheme based on channel polarization phenomenon, and it has been proved to be the only coding method that can reach the channel capacity. Then the serial cancellation decoding algorithm of polarization codes is introduced. The algorithm has the characteristics of simple structure and low complexity. Then it introduces the confidence propagation algorithm which can be used in the decoding of polarizing codes. The confidence propagation algorithm based on graph model has parallel structure, and it has shorter delay and higher throughput than the serial cancellation algorithm. It has important practical value to study this algorithm in depth. However, some of the computation involved in this algorithm is more complex, and the method of probability calculation can reduce the complexity of the original algorithm, so this paper has carried on the probability of the original algorithm and carried on a series of optimization processing, and the method of probability calculation can reduce the complexity of the original algorithm. The simulation results show that the optimized probability calculation method can achieve the same performance as the traditional algorithm. Finally, the high-precision probability calculation method based on piecewise method is used to solve the problem of long random sequence in traditional probability calculation. This method can shorten the length of probability sequence under the condition of ensuring the precision of operation. Simulation results show that this method can reduce the length of random sequences under the premise of ensuring decoding performance.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN911.22
【參考文獻(xiàn)】
相關(guān)博士學(xué)位論文 前1條
1 陳杰男;基于概率計(jì)算的無(wú)線通信DSP系統(tǒng)高效VLSI實(shí)現(xiàn)技術(shù)研究[D];電子科技大學(xué);2014年
，本文編號(hào)：2451653
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