基于概率计算的极化码译码研究
发布时间：2019-04-01 14:57
【摘要】：近些年提出的全新信道编码解决方案极化码,其相比其他现有的信道编码方法具有最优的理论性能以及较低的译码复杂度等优势,并引起需要研究人员的注意。极化码可以采用串行抵消算法或者置信传播算法进行译码,该算法在译码过程中为串行译码方式,这种译码特点结构简单、复杂度较低,但是会存在较大的译码延迟问题。基于概率推理的置信传播算法是极化码译码算法中的一种,极化码可以看作是一种基于图模型的编码方法,这个图模型中的相邻节点之间会存在概率上的依赖关系,所以可以使用置信传播的方法完成图中节点的概率推理以及更新过程,而且这种算法本身的并行运算特点也能够有效的减小延迟问题。本文主要研究了基于概率计算的极化码置信传播译码算法。首先回顾了信道编码的发展历史和有关内容,并介绍了提出极化码的背景和有关的基本知识。极化码是一种基于信道极化现象的编码方案,并且是已经被证明了能够达到信道容量的唯一编码方法。然后介绍了极化码的串行抵消译码算法,该算法有结构简单,复杂度低的特点,之后介绍了能够应用在极化码译码中的置信传播算法,基于图模型的置信传播算法具有并行结构,并且其相对于串行抵消算法具有更短时延和更高的吞吐量,深入研究该算法具有重要的实用价值。不过该算法中涉及到的一些计算较为复杂,而概率计算的方法能够降低原有算法的复杂度,所以本文对原有算法进行了概率化并进行了一系列优化处理,通过仿真结果可以得出经过优化之后的概率计算方法能够实现与传统算法相近的性能。最后基于分段方法的高精度概率计算方法被用来解决传统概率计算中随机序列较长的问题,该方法能够在保证运算精度的情况下缩短概率序列长度,仿真结果表明在保证译码性能的前提下,这种方法能够减少随机序列长度。
[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.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN911.22
本文编号：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.
【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN911.22
【参考文献】
相关博士学位论文 前1条
1 陈杰男;基于概率计算的无线通信DSP系统高效VLSI实现技术研究[D];电子科技大学;2014年
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