大规模MIMO系统信道估计方法的研究
发布时间：2018-12-12 00:57
【摘要】：大规模MIMO技术的众多优势使其成为5G通信的关键技术之一。随着天线的增多,信道矩阵维度越来越高,信道估计会更加复杂,这对信道估计算法提出了更高的要求。基于导频的信道估计方法较为简单,但导频污染会严重制约系统性能,因此研究低复杂度且能有效抗导频污染的信道估计算法就显得尤为重要。本文首先对无线信道衰落特性进行了简单的介绍,介绍了点对点大规模MIMO系统和多用户大规模MIMO系统模型。分析了无协作多小区大规模MIMO系统中存在的导频污染现象,并理论分析了导频污染产生的原因。接下来本文研究了三种基于导频的信道估计方法,其中贝叶斯信道估计方法利用了信道的统计特征,如到达角(AOA)信息,有较好的抗导频污染能力。最后通过仿真实验对比其与LS估计的性能,实验结果表明贝叶斯信道估计方法有着较好的抗导频污染能力。半盲信道估计算法仅仅需要很少的导频,这样就避免了导频污染。本文分析了基于EVD、SVD的半盲信道估计算法的原理,同时对算法的估计误差进行了推导分析。接着推导出模糊矩阵迭代计算的关系式,利用FRRH子空间跟踪算法减少了接收端信号自相关矩阵的信号子空间的计算量,然后给出了一种基于FRRH的半盲信道估计算法。通过仿真实验对这三种半盲信道估计算法的性能进行比较分析。由仿真结果得出,基于FRRH信道估计算法在牺牲较少估计性能的重要前提下,大大减少了算法的复杂度,更加适用于实际的大规模MIMO系统。
[Abstract]:Large-scale MIMO technology has become one of the key technologies of 5 G communication due to its many advantages. With the increase of antenna, the dimension of channel matrix becomes higher and higher, and the channel estimation will become more complex, which puts forward higher requirements for channel estimation algorithm. The channel estimation method based on pilot frequency is relatively simple, but pilot pollution will seriously restrict the performance of the system. Therefore, it is very important to study the channel estimation algorithm with low complexity and effective resistance to pilot pollution. In this paper, the fading characteristics of wireless channel are introduced briefly, and the models of point-to-point large-scale MIMO system and multi-user large-scale MIMO system are introduced. The pilot pollution phenomenon in large scale MIMO system without collaboration is analyzed, and the causes of pilot pollution are analyzed theoretically. Then three pilot-based channel estimation methods are studied in this paper. The Bayesian channel estimation method makes use of the statistical characteristics of the channel such as the (AOA) information of the angle of arrival and has a good ability to resist pilot pollution. Finally, the performance of Bayesian channel estimation is compared with that of LS estimation. The experimental results show that the Bayesian channel estimation method has a good ability to resist pilot pollution. The semi-blind channel estimation algorithm requires only a few pilots, thus avoiding pilot pollution. In this paper, the principle of semi-blind channel estimation algorithm based on EVD,SVD is analyzed, and the estimation error of the algorithm is deduced and analyzed. Then the relation formula of iterative calculation of fuzzy matrix is derived, and the computation of signal subspace of autocorrelation matrix at the receiving end is reduced by using FRRH subspace tracking algorithm. Then a semi-blind channel estimation algorithm based on FRRH is presented. The performance of these three semi-blind channel estimation algorithms is compared and analyzed by simulation experiments. The simulation results show that the channel estimation algorithm based on FRRH greatly reduces the complexity of the algorithm at the expense of less estimation performance and is more suitable for large scale MIMO systems.
【学位授予单位】：南京邮电大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN919.3
本文编号：2373577
[Abstract]:Large-scale MIMO technology has become one of the key technologies of 5 G communication due to its many advantages. With the increase of antenna, the dimension of channel matrix becomes higher and higher, and the channel estimation will become more complex, which puts forward higher requirements for channel estimation algorithm. The channel estimation method based on pilot frequency is relatively simple, but pilot pollution will seriously restrict the performance of the system. Therefore, it is very important to study the channel estimation algorithm with low complexity and effective resistance to pilot pollution. In this paper, the fading characteristics of wireless channel are introduced briefly, and the models of point-to-point large-scale MIMO system and multi-user large-scale MIMO system are introduced. The pilot pollution phenomenon in large scale MIMO system without collaboration is analyzed, and the causes of pilot pollution are analyzed theoretically. Then three pilot-based channel estimation methods are studied in this paper. The Bayesian channel estimation method makes use of the statistical characteristics of the channel such as the (AOA) information of the angle of arrival and has a good ability to resist pilot pollution. Finally, the performance of Bayesian channel estimation is compared with that of LS estimation. The experimental results show that the Bayesian channel estimation method has a good ability to resist pilot pollution. The semi-blind channel estimation algorithm requires only a few pilots, thus avoiding pilot pollution. In this paper, the principle of semi-blind channel estimation algorithm based on EVD,SVD is analyzed, and the estimation error of the algorithm is deduced and analyzed. Then the relation formula of iterative calculation of fuzzy matrix is derived, and the computation of signal subspace of autocorrelation matrix at the receiving end is reduced by using FRRH subspace tracking algorithm. Then a semi-blind channel estimation algorithm based on FRRH is presented. The performance of these three semi-blind channel estimation algorithms is compared and analyzed by simulation experiments. The simulation results show that the channel estimation algorithm based on FRRH greatly reduces the complexity of the algorithm at the expense of less estimation performance and is more suitable for large scale MIMO systems.
【学位授予单位】：南京邮电大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TN919.3
【参考文献】
相关期刊论文 前1条
1 YAO Tianqi;LI Yong;;Pilot Contamination Reduction by Shifted Frame Structure in Massive MIMO TDD Wireless System[J];Wuhan University Journal of Natural Sciences;2015年03期
，本文编号：2373577
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