高阶QAM通信系统中相位噪声抑制算法研究
发布时间：2018-12-18 00:29
【摘要】：近年来,随着移动互联网、大数据、云计算、物联网等新兴技术的迅猛发展,网络流量高速增长,人们对带宽的需求越来越大,如何进一步提升通信系统的传输容量成为了研究热点,由于频谱资源的有限性,提高频谱效率成为了提高通信系统传输容量的有效方法。高阶正交振幅调制(M-QAM)由于具有多阶和多维调制和编码特性而成为提高系统传输容量的最具吸引力的调制方式。然而随着调制阶数的增加,星座图中的点将会变得更加密集,这时除了加性白噪声之外,相位噪声也将明显影响系统的性能。本文主要对高阶QAM通信系统中的相位噪声抑制算法进行了研究,主要研究工作和成果如下:1.对通信系统中相位噪声的来源及表示方法进行了详细的理论分析,并对常用的相位噪声模型进行了分类,使用Matlab对高阶QAM通信系统中相位噪声的影响进行了仿真分析。2.重点研究了通信系统中不同模块的相位噪声抑制算法并将其分为三类,分析了各类算法中几种典型算法的原理以及流程并归纳了各自的优缺点,搭建Matlab平台仿真对比了各类算法中几种典型算法的误码率性能,结果表明,在发送端通过对星座图进行优化的算法中,圆形对称的QAM星座图结构有最好的误码率性能;在载波恢复模块对相位噪声进行抑制的算法中,基于数据辅助的维纳内插算法的误码率性能要大大优于非数据辅助算法中的幂律算法;在改进的硬判决算法中,算法的误码性能与相位噪声对系统的影响因子α有着重要关系;在改进的软判决算法中,改进后的算法的误码性能要优于标准软判决算法。3.针对现代通信系统中智能化这一趋势,本文提出了一种基于改进的引力搜索算法的相位噪声抑制算法,并用Matlab软件对它仿真,从迭代次数和惯性因子两个角度对算法进行了详细分析,结果表明迭代次数越高时,该算法的精度越高;在惯性因子k取值为动态调整时算法可获得最快的收敛速度,符号群能在最短时间内找到各自的最优位置。
[Abstract]:In recent years, with the rapid development of mobile Internet, big data, cloud computing, Internet of things and other emerging technologies, network traffic is growing at a high speed, and the demand for bandwidth is increasing. How to further enhance the transmission capacity of communication systems has become a hot topic. Because of the limitation of spectrum resources, improving spectrum efficiency has become an effective method to improve the transmission capacity of communication systems. High order quadrature amplitude modulation (M-QAM) is the most attractive modulation method for improving the transmission capacity of the system due to its multi-order and multi-dimensional modulation and coding characteristics. However, with the increase of modulation order, the points in the constellation will become more dense. In addition to the additive white noise, the phase noise will obviously affect the performance of the system. In this paper, phase noise suppression algorithms in high order QAM communication systems are studied. The main work and results are as follows: 1. The origin and representation of phase noise in communication system are analyzed in detail, and the commonly used phase noise models are classified. The effect of phase noise in high order QAM communication system is simulated by using Matlab. 2. The phase noise suppression algorithms of different modules in communication system are studied and classified into three categories. The principle and flow of several typical algorithms are analyzed and their advantages and disadvantages are summarized. The BER performance of several typical algorithms is compared by building a Matlab platform. The results show that the circular symmetric QAM constellation structure has the best BER performance in the algorithm of constellation diagram optimization. In the algorithm of phase noise suppression in carrier recovery module, the BER performance of Wiener interpolation algorithm based on data assistance is much better than that of power law algorithm in non-data-aided algorithm. In the improved hard decision algorithm, the error performance of the algorithm has an important relationship with the influence factor 伪 of phase noise on the system, and in the improved soft decision algorithm, the error performance of the improved algorithm is better than that of the standard soft decision algorithm. Aiming at the trend of intelligence in modern communication system, this paper presents a phase noise suppression algorithm based on improved gravitational search algorithm, and simulates it with Matlab software. The algorithm is analyzed in detail from the angles of iteration number and inertia factor. The results show that the higher the iteration number, the higher the accuracy of the algorithm. When the inertia factor k is dynamically adjusted, the algorithm can obtain the fastest convergence speed, and the symbol group can find their optimal position in the shortest time.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN914
本文编号：2385010
[Abstract]:In recent years, with the rapid development of mobile Internet, big data, cloud computing, Internet of things and other emerging technologies, network traffic is growing at a high speed, and the demand for bandwidth is increasing. How to further enhance the transmission capacity of communication systems has become a hot topic. Because of the limitation of spectrum resources, improving spectrum efficiency has become an effective method to improve the transmission capacity of communication systems. High order quadrature amplitude modulation (M-QAM) is the most attractive modulation method for improving the transmission capacity of the system due to its multi-order and multi-dimensional modulation and coding characteristics. However, with the increase of modulation order, the points in the constellation will become more dense. In addition to the additive white noise, the phase noise will obviously affect the performance of the system. In this paper, phase noise suppression algorithms in high order QAM communication systems are studied. The main work and results are as follows: 1. The origin and representation of phase noise in communication system are analyzed in detail, and the commonly used phase noise models are classified. The effect of phase noise in high order QAM communication system is simulated by using Matlab. 2. The phase noise suppression algorithms of different modules in communication system are studied and classified into three categories. The principle and flow of several typical algorithms are analyzed and their advantages and disadvantages are summarized. The BER performance of several typical algorithms is compared by building a Matlab platform. The results show that the circular symmetric QAM constellation structure has the best BER performance in the algorithm of constellation diagram optimization. In the algorithm of phase noise suppression in carrier recovery module, the BER performance of Wiener interpolation algorithm based on data assistance is much better than that of power law algorithm in non-data-aided algorithm. In the improved hard decision algorithm, the error performance of the algorithm has an important relationship with the influence factor 伪 of phase noise on the system, and in the improved soft decision algorithm, the error performance of the improved algorithm is better than that of the standard soft decision algorithm. Aiming at the trend of intelligence in modern communication system, this paper presents a phase noise suppression algorithm based on improved gravitational search algorithm, and simulates it with Matlab software. The algorithm is analyzed in detail from the angles of iteration number and inertia factor. The results show that the higher the iteration number, the higher the accuracy of the algorithm. When the inertia factor k is dynamically adjusted, the algorithm can obtain the fastest convergence speed, and the symbol group can find their optimal position in the shortest time.
【学位授予单位】：北京交通大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN914
【参考文献】
相关硕士学位论文 前3条
1 杨国翔;QAM系统中抑制相位噪声算法的研究[D];西安电子科技大学;2014年
2 袁亚玲;基于星座图设计的相位噪声抑制算法研究[D];西安电子科技大学;2012年
3 喻勤;高阶调制系统中相位噪声抑制算法研究[D];西安电子科技大学;2012年
，本文编号：2385010
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