多天线系统中基于子空间的盲信道估计算法研究
发布时间：2018-08-06 10:44
【摘要】：多天线技术通过在发射端或接收端安装多个天线,显著提升通信系统的容量、覆盖范围和频谱利用率,成为目前无线通信领域中极受关注的技术。信道均衡作为无线通信的一个重要环节,利用信道状态信息补偿信道对发送信号的影响。而由于无线移动信道具有未知时变的特性,因此要求接收端事先对信道状态信息进行估计。传统的做法是通过周期性地发送训练序列来获取信道的相关信息,不仅降低了频带利用率,而且限制了其在某些无法发送训练序列的场景中的应用。不同于传统做法,盲和半盲的信道估计方法不需要或仅需要少量的训练序列就可以完成信道估计。本文针对多天线系统中的盲信道估计这一课题,重点关注基于子空间的盲信道估计方法,研究内容概述如下:1.研究了现有多天线系统中的盲信道估计方法,根据方法中所用到的接收信号的统计特性类型进行分类,总结各类算法的研究现状,并对各自的优缺点及适用场景进行分析,进而突出体现基于子空间类算法的优势。2.研究了频率选择性衰落信道下单发多收系统中的信道阶数盲估计问题,在总结经典阶数盲估计方法的基础上,针对几种经典算法对信噪比条件要求严苛或在信道有首尾系数时性能恶化的不足,将之前被人们用于信源数估计的盖尔圆准则应用于解决信道阶数估计问题,提出了一种新的信道阶数估计方法。3.研究了SIMO系统中基于子空间的盲信道估计方法,针对传统算法仅能处理已知精确信道阶数情况下信道估计问题的不足,通过利用有理空间理论对传统算法进行改进,将其应用扩展到了已知信道阶数上界的情况,从而使基于子空间的算法对信道阶数过估计具有鲁棒性,增强了算法的实用性。4.对基于子空间的盲信道估计算法在利用空时分组编码的多天线系统中的应用进行了研究。重点讨论了空时分组编码系统中的信道可盲辨识条件,并针对模糊度问题,利用半盲信道估计的思想,通过借助少量训练序列实现了信道的完全辨识,使接收端能够完成对发送信号的正确解码。5.模糊度是盲信道估计固有的问题,由于这一问题不能通过全盲的方法解决,因此在许多研究盲信道估计算法的文献中往往被一带而过,但这一问题会对实际通信产生严重影响。本文在研究SIMO系统和空时分组编码系统下的信道盲辨识时,重点关注了模糊度问题,分析了模糊度在不同系统下的表现形式。
[Abstract]:By installing multiple antennas at the transmitter or receiver, the multi-antenna technology has become the most concerned technology in the wireless communication field, which can significantly improve the capacity, coverage and spectrum efficiency of the communication system. As an important part of wireless communication, channel equalization compensates the influence of channel on the transmitted signal by using channel state information. Due to the unknown time-varying characteristics of the wireless mobile channel, the receiver is required to estimate the channel state information in advance. The traditional method is to obtain the relevant information of the channel by sending the training sequence periodically, which not only reduces the frequency band efficiency, but also limits its application in some scenes where the training sequence cannot be transmitted. Different from traditional methods, blind and semi-blind channel estimation methods need not or only a small number of training sequences to complete channel estimation. This paper focuses on the blind channel estimation in multi-antenna systems, focusing on the subspace-based blind channel estimation. The research contents are summarized as follows: 1. The existing blind channel estimation methods in multi-antenna systems are studied. The methods are classified according to the statistical characteristic types of received signals used in the methods, and the research status of various algorithms is summarized, and their advantages and disadvantages and applicable scenarios are analyzed. And then highlight the advantages of subspace class algorithm. 2. In this paper, the blind estimation of channel order in frequency selective fading channel is studied. In order to solve the problem of channel order estimation, the Gaelic circle criterion, which was previously used to estimate the number of sources, is applied to solve the problem of channel order estimation, aiming at the shortcomings of several classical algorithms that require strict SNR conditions or deteriorate performance when the channel has first and last coefficients. A new channel order estimation method. The blind channel estimation method based on subspace in SIMO system is studied. The traditional algorithm is improved by using rational space theory to solve the problem of channel estimation only in the case of known accurate channel order. Its application is extended to the case where the upper bound of the channel order is known, so that the subspace-based algorithm is robust to the channel order overestimation, and the practicability of the algorithm is enhanced. The application of subspace-based blind channel estimation algorithm in space-time block coding multi-antenna systems is studied. In this paper, the blind identification condition of channel in space-time block coding system is discussed. Aiming at the ambiguity problem, the complete channel identification is realized by means of a small number of training sequences, using the idea of semi-blind channel estimation. Enables the receiver to complete the correct decoding of the transmitted signal. 5. Ambiguity is an inherent problem in blind channel estimation. Because this problem can not be solved by all-blind methods, it is often mentioned in many literatures that study blind channel estimation algorithms, but this problem will have a serious impact on the actual communication. In this paper, when we study the blind channel identification in SIMO system and space-time block coding system, we focus on the ambiguity problem and analyze the representation of ambiguity in different systems.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN820;TN911.22
[Abstract]:By installing multiple antennas at the transmitter or receiver, the multi-antenna technology has become the most concerned technology in the wireless communication field, which can significantly improve the capacity, coverage and spectrum efficiency of the communication system. As an important part of wireless communication, channel equalization compensates the influence of channel on the transmitted signal by using channel state information. Due to the unknown time-varying characteristics of the wireless mobile channel, the receiver is required to estimate the channel state information in advance. The traditional method is to obtain the relevant information of the channel by sending the training sequence periodically, which not only reduces the frequency band efficiency, but also limits its application in some scenes where the training sequence cannot be transmitted. Different from traditional methods, blind and semi-blind channel estimation methods need not or only a small number of training sequences to complete channel estimation. This paper focuses on the blind channel estimation in multi-antenna systems, focusing on the subspace-based blind channel estimation. The research contents are summarized as follows: 1. The existing blind channel estimation methods in multi-antenna systems are studied. The methods are classified according to the statistical characteristic types of received signals used in the methods, and the research status of various algorithms is summarized, and their advantages and disadvantages and applicable scenarios are analyzed. And then highlight the advantages of subspace class algorithm. 2. In this paper, the blind estimation of channel order in frequency selective fading channel is studied. In order to solve the problem of channel order estimation, the Gaelic circle criterion, which was previously used to estimate the number of sources, is applied to solve the problem of channel order estimation, aiming at the shortcomings of several classical algorithms that require strict SNR conditions or deteriorate performance when the channel has first and last coefficients. A new channel order estimation method. The blind channel estimation method based on subspace in SIMO system is studied. The traditional algorithm is improved by using rational space theory to solve the problem of channel estimation only in the case of known accurate channel order. Its application is extended to the case where the upper bound of the channel order is known, so that the subspace-based algorithm is robust to the channel order overestimation, and the practicability of the algorithm is enhanced. The application of subspace-based blind channel estimation algorithm in space-time block coding multi-antenna systems is studied. In this paper, the blind identification condition of channel in space-time block coding system is discussed. Aiming at the ambiguity problem, the complete channel identification is realized by means of a small number of training sequences, using the idea of semi-blind channel estimation. Enables the receiver to complete the correct decoding of the transmitted signal. 5. Ambiguity is an inherent problem in blind channel estimation. Because this problem can not be solved by all-blind methods, it is often mentioned in many literatures that study blind channel estimation algorithms, but this problem will have a serious impact on the actual communication. In this paper, when we study the blind channel identification in SIMO system and space-time block coding system, we focus on the ambiguity problem and analyze the representation of ambiguity in different systems.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN820;TN911.22
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