【摘要】：多天線技術(shù)通過在發(fā)射端或接收端安裝多個(gè)天線,顯著提升通信系統(tǒng)的容量、覆蓋范圍和頻譜利用率,成為目前無線通信領(lǐng)域中極受關(guān)注的技術(shù)。信道均衡作為無線通信的一個(gè)重要環(huán)節(jié),利用信道狀態(tài)信息補(bǔ)償信道對(duì)發(fā)送信號(hào)的影響。而由于無線移動(dòng)信道具有未知時(shí)變的特性,因此要求接收端事先對(duì)信道狀態(tài)信息進(jìn)行估計(jì)。傳統(tǒng)的做法是通過周期性地發(fā)送訓(xùn)練序列來獲取信道的相關(guān)信息,不僅降低了頻帶利用率,而且限制了其在某些無法發(fā)送訓(xùn)練序列的場景中的應(yīng)用。不同于傳統(tǒng)做法,盲和半盲的信道估計(jì)方法不需要或僅需要少量的訓(xùn)練序列就可以完成信道估計(jì)。本文針對(duì)多天線系統(tǒng)中的盲信道估計(jì)這一課題,重點(diǎn)關(guān)注基于子空間的盲信道估計(jì)方法,研究內(nèi)容概述如下:1.研究了現(xiàn)有多天線系統(tǒng)中的盲信道估計(jì)方法,根據(jù)方法中所用到的接收信號(hào)的統(tǒng)計(jì)特性類型進(jìn)行分類,總結(jié)各類算法的研究現(xiàn)狀,并對(duì)各自的優(yōu)缺點(diǎn)及適用場景進(jìn)行分析,進(jìn)而突出體現(xiàn)基于子空間類算法的優(yōu)勢(shì)。2.研究了頻率選擇性衰落信道下單發(fā)多收系統(tǒng)中的信道階數(shù)盲估計(jì)問題,在總結(jié)經(jīng)典階數(shù)盲估計(jì)方法的基礎(chǔ)上,針對(duì)幾種經(jīng)典算法對(duì)信噪比條件要求嚴(yán)苛或在信道有首尾系數(shù)時(shí)性能惡化的不足,將之前被人們用于信源數(shù)估計(jì)的蓋爾圓準(zhǔn)則應(yīng)用于解決信道階數(shù)估計(jì)問題,提出了一種新的信道階數(shù)估計(jì)方法。3.研究了SIMO系統(tǒng)中基于子空間的盲信道估計(jì)方法,針對(duì)傳統(tǒng)算法僅能處理已知精確信道階數(shù)情況下信道估計(jì)問題的不足,通過利用有理空間理論對(duì)傳統(tǒng)算法進(jìn)行改進(jìn),將其應(yīng)用擴(kuò)展到了已知信道階數(shù)上界的情況,從而使基于子空間的算法對(duì)信道階數(shù)過估計(jì)具有魯棒性,增強(qiáng)了算法的實(shí)用性。4.對(duì)基于子空間的盲信道估計(jì)算法在利用空時(shí)分組編碼的多天線系統(tǒng)中的應(yīng)用進(jìn)行了研究。重點(diǎn)討論了空時(shí)分組編碼系統(tǒng)中的信道可盲辨識(shí)條件,并針對(duì)模糊度問題,利用半盲信道估計(jì)的思想,通過借助少量訓(xùn)練序列實(shí)現(xiàn)了信道的完全辨識(shí),使接收端能夠完成對(duì)發(fā)送信號(hào)的正確解碼。5.模糊度是盲信道估計(jì)固有的問題,由于這一問題不能通過全盲的方法解決,因此在許多研究盲信道估計(jì)算法的文獻(xiàn)中往往被一帶而過,但這一問題會(huì)對(duì)實(shí)際通信產(chǎn)生嚴(yán)重影響。本文在研究SIMO系統(tǒng)和空時(shí)分組編碼系統(tǒng)下的信道盲辨識(shí)時(shí),重點(diǎn)關(guān)注了模糊度問題,分析了模糊度在不同系統(tǒng)下的表現(xiàn)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.
【學(xué)位授予單位】：西安電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN820;TN911.22

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本文編號(hào)：2167486