本文選題：半盲信道估計(jì)　切入點(diǎn)：MIMO　出處：《電子科技大學(xué)》2014年碩士論文

【摘要】：在無(wú)線通信系統(tǒng)中,為了獲得更大的性能優(yōu)勢(shì),往往需要準(zhǔn)確的估計(jì)出無(wú)線信道參數(shù)。目前常用的信道估計(jì)方法可以歸納為三類(lèi):基于訓(xùn)練符的信道估計(jì)方法、盲信道估計(jì)方法和半盲信道估計(jì)方法�；谟�(xùn)練符的信道估計(jì)方法相對(duì)簡(jiǎn)單,但是頻帶利用率低;盲信道估計(jì)方法頻帶利用率高,但是相應(yīng)的計(jì)算復(fù)雜度也大;半盲信道估計(jì)方法結(jié)合了盲信道估計(jì)和非盲信道估計(jì)方法的優(yōu)點(diǎn),有著一定的優(yōu)勢(shì)。因此,頻帶利用率、算法復(fù)雜度以及估計(jì)精度是設(shè)計(jì)信道估計(jì)算法時(shí)需要綜合考慮的三個(gè)關(guān)鍵問(wèn)題。本文針對(duì)使用OSTBC技術(shù)的多用戶MIMO-CDMA系統(tǒng),提出了一種新的半盲信道估計(jì)算法。首先,本文對(duì)基于訓(xùn)練符的LS信道估計(jì)算法和基于MUSIC的半盲信道估計(jì)算法進(jìn)行了詳細(xì)的研究,分析這兩種信道估計(jì)算法的優(yōu)缺點(diǎn),包括頻帶利用率和算法性能,并進(jìn)行了試驗(yàn)仿真驗(yàn)證。然后,提出了一種使用OSTBC技術(shù)的多用戶MIMO-CDMA系統(tǒng)模型,對(duì)該模型進(jìn)行了詳細(xì)的分析說(shuō)明。針對(duì)該系統(tǒng)模型,在MUSIC算法的研究基礎(chǔ)上提出了一種基于向量空間投影的半盲信道估計(jì)算法。在算法的推導(dǎo)過(guò)程中,證明了需要估計(jì)的信道信息向量屬于兩個(gè)非正交的子空間,并利用向量空間投影理論求得該向量。在具體的計(jì)算過(guò)程中,通過(guò)對(duì)正交投影矩陣的分析,結(jié)合矩陣特征值、特征向量的性質(zhì)提出了一種單步解方法,減小了算法的復(fù)雜度。該算法僅使用了一組已知的訓(xùn)練符,便解決了估計(jì)量符號(hào)模糊問(wèn)題,沒(méi)有增加系統(tǒng)的復(fù)雜度,也沒(méi)有對(duì)系統(tǒng)頻帶利用率產(chǎn)生影響。最后,通過(guò)仿真實(shí)驗(yàn)證明了本文提出的算法相比于基于訓(xùn)練符的LS信道估計(jì)算法有更高的估計(jì)精度和更低的誤碼率。本文的創(chuàng)新點(diǎn)概括如下:(1)提出了一種單步解方法,該方法將求一個(gè)維度較大矩陣的主特征向量轉(zhuǎn)向求一個(gè)維度不大的矩陣主特征向量,有效減小了算法的計(jì)算復(fù)雜度;(2)通過(guò)對(duì)系統(tǒng)模型的研究,論證了需要估計(jì)的復(fù)合信道信息向量屬于兩個(gè)非正交的子空間,并使用向量空間投影的方法直接計(jì)算得到復(fù)合信道信息,避免了基于MUSIC和LS的信道估計(jì)方法中需要估計(jì)過(guò)多參數(shù)的問(wèn)題;
[Abstract]:In order to gain more performance advantages in wireless communication systems, it is often necessary to estimate the wireless channel parameters accurately. The commonly used channel estimation methods can be classified into three categories: Channel estimation methods based on training characters, Blind channel estimation method and semi-blind channel estimation method. The channel estimation method based on training symbol is relatively simple, but the frequency band efficiency is low, the blind channel estimation method has high frequency band efficiency, but the corresponding computational complexity is also large. The semi-blind channel estimation method combines the advantages of the blind channel estimation method and the non-blind channel estimation method. Algorithm complexity and estimation accuracy are three key problems to be considered when designing channel estimation algorithms. In this paper, a new semi-blind channel estimation algorithm is proposed for multi-user MIMO-CDMA systems using OSTBC technology. In this paper, the LS channel estimation algorithm based on training symbol and semi-blind channel estimation algorithm based on MUSIC are studied in detail, and the advantages and disadvantages of these two channel estimation algorithms are analyzed, including frequency band efficiency and algorithm performance. Then, a multi-user MIMO-CDMA system model using OSTBC technology is proposed, and the model is analyzed in detail. Based on the research of MUSIC algorithm, a semi-blind channel estimation algorithm based on vector space projection is proposed. In the derivation of the algorithm, it is proved that the channel information vector that needs to be estimated belongs to two non-orthogonal subspaces. The vector is obtained by using the vector space projection theory. In the process of calculation, a one-step method is proposed by analyzing the orthogonal projection matrix and combining the eigenvalues of the matrix and the properties of the eigenvector. The complexity of the algorithm is reduced. The algorithm only uses a set of known training symbols, which solves the ambiguity problem of the estimator symbol, does not increase the complexity of the system, nor does it affect the frequency band efficiency of the system. Finally, The simulation results show that the proposed algorithm has higher estimation accuracy and lower bit error rate than the LS channel estimation algorithm based on training characters. The innovation of this paper is summarized as follows: 1) A one-step method is proposed. In this method, the principal eigenvector of a large dimension matrix is changed to the principal eigenvector of a small dimension matrix, which effectively reduces the computational complexity of the algorithm. It is proved that the complex channel information vector that needs to be estimated belongs to two non-orthogonal subspaces, and the compound channel information is directly calculated by vector space projection method. The problem of estimating too many parameters in channel estimation method based on MUSIC and LS is avoided.
【學(xué)位授予單位】：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(lèi)號(hào)】：TN929.533

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