自由空间光通信中LDPC码低复杂度译码算法研究

发布时间：2018-02-08 16:04

本文关键词： 自由空间光通信低密度奇偶校验码 Gamma-Gamma分布对数域BP算法归一化最小和算法　出处：《吉林大学》2017年硕士论文　论文类型：学位论文

【摘要】：自由空间光(Free Space Optical,FSO)通信是一种新型的无线通信方式,作为最后一公里解决方案已经成为近年来研究的热点,它以激光作为载体把信息加载到激光上发送到大气进行传输。FSO通信具有广泛的应用领域。例如:深空通信、中轨道、地面之间的复杂地形导致的其它通信方式实现困难的通信,在一些特殊情况下还可以进行地面与卫星之间的通信,一般情况下把地面之间的激光通信称为“大气激光通信”。FSO通信系统之所以受到越来越多学者们的青睐,主要是因为这种通信技术具有如下优势:它具有相当高的传输速率,不亚于光纤的传输速率,在一些特殊情况下,FSO通信的最高通信速率可达到56 Gb/s;FSO通信技术不受带宽的限制,相对于射频无线通信在频谱资源上有着很大的优势。虽然FSO通信技术具有诸多优势,在其发展中也存在着技术瓶颈。在激光通信中,大气的影响和光强起伏是限制通信质量和通信距离的主要原因。为了抑制大气对通信性能的不良作用,国内外的学者们在不同方面进行了研究,其中主要技术有:光源技术、自适应校正技术、编码与调制技术等,其中信道编译码是本文研究的重点。低密度奇偶校验(Low Density Parity Check,LDPC)码是具有逼近Shannon极限性能的好码型,它具有极低的错误平层。由于性能优异,使得LDPC码在无线通信领域应用广泛,并成为第四代移动通信的标准之一。但是,对它在自由空间光通信领域中的应用研究还具有很大的挖掘空间,本文正是以此为出发点展开的。本文首先介绍了大气激光通信的相关理论知识。在介绍了几种基本的信道模型后,详细分析了大气中各种噪声,并给出了大气信道模型。综合各种大气湍流信道噪声对通信链路造成的干扰,采用了与实测数据较为一致的Gamma-Gamma分布作为信道模型。研究了LDPC码的结构和校验矩阵的构造方法和LDPC码的几种迭代译码算法,包括概率域BP算法、对数域BP(LLR BP)算法、最小和(Min Sum)算法、归一化最小和算法、迭代APP算法等多种算法,提出了一种基于归一化最小和算法的改进算法,并在各种湍流强度信道下对各译码算法在复杂度和性能上进行了比较和仿真分析。然后在Gamma-Gamma信道模型上对几种译码算法进行了仿真比较,分析所提出的改进算法相比于最小和算法、LLR BP算法的性能提升。最后讨论了迭代次数和码长选取对译码性能的影响。
[Abstract]:Free Space Optical Space (FSO) communication is a new type of wireless communication. As a last kilometer solution, it has become a hot research topic in recent years. It takes the laser as the carrier to load the information into the laser and send it to the atmosphere for transmission. FSO communication has a wide range of applications. For example: deep space communication, intermediate orbit, complex terrain between the ground caused by other means of communication to achieve difficult communication, In some special cases, it is possible to communicate between the ground and the satellite. Generally speaking, the laser communication between the ground and the earth is called "atmospheric laser communication" .FSO communication system is favored by more and more scholars. The main reason is that this kind of communication technology has the following advantages: it has quite high transmission rate, no less than the transmission rate of optical fiber, and in some special cases the highest communication rate of FSO communication can reach 56Gb / s / FSO communication technology, which is not limited by bandwidth. Compared with RF wireless communication, it has a great advantage in spectrum resources. Although FSO communication technology has many advantages, there are also technical bottlenecks in its development. The influence of atmosphere and the fluctuation of light intensity are the main reasons for limiting the communication quality and communication distance. In order to restrain the adverse effect of atmosphere on the communication performance, scholars at home and abroad have carried out research in different aspects, among which the main technologies are: light source technology, Adaptive correction techniques, coding and modulation techniques, among which channel coding and decoding are the focus of this paper. Low density parity check low Density Parity check LDPCs are good codes with the performance of approaching the limit of Shannon. Because of its excellent performance, LDPC codes are widely used in wireless communication field and become one of the 4th generation mobile communication standards. The research on its application in the field of free space optical communication also has great space for mining. This paper first introduces the relevant theoretical knowledge of atmospheric laser communication. After introducing several basic channel models, the noise in the atmosphere is analyzed in detail. The model of atmospheric channel is given, which synthesizes the interference of various atmospheric turbulence channel noise to the communication link. The Gamma-Gamma distribution, which is consistent with the measured data, is used as the channel model. The structure of the LDPC code and the construction of the check matrix and several iterative decoding algorithms of the LDPC code are studied, including the probabilistic BP algorithm and the logarithmic BP(LLR BP algorithm. This paper presents an improved algorithm based on normalized minimum sum algorithm, normalized minimum sum algorithm, iterative APP algorithm and so on. The complexity and performance of each decoding algorithm are compared and simulated in various turbulent intensity channels. Then several decoding algorithms are simulated and compared on the Gamma-Gamma channel model. Compared with the minimum sum algorithm, the performance of the improved algorithm is improved. Finally, the influence of the number of iterations and code length on the decoding performance is discussed.
【学位授予单位】：吉林大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN929.1;TN911.22

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