MIMO无线通信系统中的信号检测技术研究

发布时间：2018-01-16 21:31

本文关键词：MIMO无线通信系统中的信号检测技术研究　出处：《华东理工大学》2014年硕士论文　论文类型：学位论文

【摘要】：随着信息技术的不断发展,人类对通信系统在高速率和大容量等方面的要求也在不断变高,传统的无线通信系统己不能满足这些要求。作为4G关键技术的多输入多输出(MIMO)技术能够在不增加额外带宽的情况下有效地提高通信系统的信道容量和无线信号的传输速率。但由于MIMO系统在收发端均采用多天线,使系统变得复杂,尤其是增大了接收机信号检测的难度。因此接收端检测技术的误码率(BER)性能和算法复杂度将直接影响MIMO通信系统的质量。本文的研究重点是MIMO系统的信号检测算法。本文首先简单介绍了MIMO系统的基本原理,分析了MIMO系统的信道容量。其次介绍了各种空时码模型和编码方案,分析了最大似然(ML)检测、迫零(ZF)检测、最小均方误差(MMSE)检测和排序串行干扰相消(OSIC)检测四种算法的译码性能和算法复杂度。针对最大似然检测算法复杂度高和另三种算法译码性能差的缺点,本文引入球形译码(SD)算法并分析了几种基本的SD算法,然后重点研究了基于概率裁剪的球形译码(SPSD)算法并提出了两种改进型SPSD算法,第一种优化算法主要将两种裁剪规则函数相结合,第二种优化算法主要利用信道矩阵预处理,通过这些方法可以进一步减少SPSD算法的复杂度。最后的仿真结果表明,在MIMO系统中,两种改进型的SPSD算法都能够逼近ML检测算法的性能,并有效减少算法复杂度,很好地达到检测算法性能和复杂度之间的折中。
[Abstract]:With the development of information technology, the requirements of communication system in high speed and large capacity are becoming higher and higher. The traditional wireless communication system can no longer meet these requirements. As a key technology of 4G, multi-input and multi-output MIMOs can not meet these requirements. The technique can effectively improve the channel capacity and wireless signal transmission rate without increasing the additional bandwidth. However, the MIMO system uses multiple antennas at the transceiver. It makes the system more complex, especially increases the difficulty of receiver signal detection, so the performance and algorithm complexity of receiver detection technology will directly affect the quality of MIMO communication system. This paper focuses on the signal detection algorithm of MIMO system. Firstly, this paper introduces the basic principle of MIMO system. The channel capacity of MIMO system is analyzed. Secondly, various space-time code models and coding schemes are introduced, and the maximum likelihood (MLL) detection and zero-forcing MIMO detection are analyzed. Minimum mean Square error (MMSE) Detection and sequencing Serial interference cancellation (OSIC). To detect the decoding performance and complexity of the four algorithms, aiming at the shortcomings of the high complexity of the maximum likelihood detection algorithm and the poor decoding performance of the other three algorithms. In this paper, the spherical decoding algorithm is introduced and several basic SD algorithms are analyzed. Then, the probabilistic clipping based sphere decoding algorithm is studied and two improved SPSD algorithms are proposed. The first optimization algorithm mainly combines two kinds of clipping rule functions. The second optimization algorithm mainly uses channel matrix preprocessing. Through these methods, the complexity of SPSD algorithm can be further reduced. Finally, the simulation results show that in MIMO system, two improved SPSD algorithms can approach the performance of ML detection algorithm. And reduce the complexity of the algorithm effectively, and achieve a good compromise between the performance and complexity of the detection algorithm.
【学位授予单位】：华东理工大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN919.3

【共引文献】