本文選題：導(dǎo)頻輔助　切入點(diǎn)：正交頻分復(fù)用　出處：《江西理工大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：正交頻分復(fù)用技術(shù)(OFDM)作為移動(dòng)通信技術(shù)領(lǐng)域內(nèi)的核心技術(shù)之一,以其獨(dú)有的傳輸速率快、抗多徑衰落能力強(qiáng)以及頻帶利用率高等特點(diǎn)被眾多專家學(xué)者認(rèn)為是未來通信發(fā)展方向的研究重點(diǎn)。而信道估計(jì)作為OFDM技術(shù)內(nèi)的重要構(gòu)成部份,目的是為了保證能夠較為精確地在接收端還原出信道的狀態(tài)信息,以提升系統(tǒng)的整體通信質(zhì)量。本文主要是圍繞基于導(dǎo)頻輔助的OFDM無線信道估計(jì)模型而進(jìn)行的研究,主要的研究工作與創(chuàng)新點(diǎn)如下:(1)對(duì)信號(hào)在無線信道內(nèi)的傳輸特性進(jìn)行了研究,詳細(xì)地介紹了多徑衰落的統(tǒng)計(jì)特性,并給出了信道的沖激響應(yīng)模型。對(duì)OFDM相關(guān)核心技術(shù)進(jìn)行了研究,重點(diǎn)討論了它的基本工作原理、系統(tǒng)結(jié)構(gòu)模型及其重要組成部份,圍繞OFDM技術(shù)內(nèi)基于導(dǎo)頻輔助的無線信道估計(jì)模型進(jìn)行了深入地探討,分析了塊狀、梳狀以及散狀三類導(dǎo)頻的結(jié)構(gòu),重點(diǎn)對(duì)LS、MMSE、LMMSE與SVD-LMMSE四類較為典型的導(dǎo)頻位置處信道估計(jì)方式進(jìn)行了研究,并介紹了幾類子載波位置處較為常見的插值方案。(2)對(duì)傳統(tǒng)的LMMSE算法進(jìn)行了細(xì)致地研究,由于其在對(duì)信道響應(yīng)進(jìn)行估計(jì)的過程中,必須要對(duì)繁復(fù)的矩陣進(jìn)行求解計(jì)算,并且需要提前知道信道的統(tǒng)計(jì)特性,針對(duì)這一問題文中基于信道能量分布的稀疏性特征引入了加權(quán)系數(shù)平均法來解決,在此基礎(chǔ)上聯(lián)合小波對(duì)符號(hào)進(jìn)行處理,并進(jìn)行實(shí)驗(yàn)仿真設(shè)計(jì)。結(jié)果表明,改進(jìn)信道估計(jì)模型的整體性能要優(yōu)于傳統(tǒng)的LS算法、SVD-LMMSE算法、LMMSE算法以及僅通過加權(quán)系數(shù)平均法改進(jìn)的LMMSE算法。(3)對(duì)傳統(tǒng)的SVD-LMMSE算法進(jìn)行了深入地研究,雖然其對(duì)傳統(tǒng)的LMMSE算法做出了簡(jiǎn)化地處理,但是卻存在著信道估計(jì)誤差較大的問題,針對(duì)這一缺陷文中聯(lián)合引入小波與經(jīng)驗(yàn)?zāi)B(tài)分解法來進(jìn)行克服,在此基礎(chǔ)上再加入閾值門限對(duì)符號(hào)進(jìn)行處理。最后,進(jìn)行實(shí)驗(yàn)的仿真設(shè)計(jì),結(jié)果表明,改進(jìn)信道估計(jì)模型的整體性能要優(yōu)于傳統(tǒng)的LS算法、LMMSE算法以及目前較為流行的SVD-LMMSE信道估計(jì)算法。
[Abstract]:OFDM (orthogonal Frequency Division Multiplexing) is one of the core technologies in the field of mobile communication. The characteristics of strong anti-multipath fading ability and high bandwidth efficiency are considered by many experts and scholars to be the focus of future communication development. Channel estimation is an important part of OFDM technology. The purpose of this paper is to ensure that the channel state information can be accurately restored at the receiver to improve the overall communication quality of the system. This paper mainly focuses on the pilot assisted OFDM wireless channel estimation model. The main research work and innovation are as follows: (1) the transmission characteristics of signals in wireless channels are studied, and the statistical characteristics of multipath fading are introduced in detail. The impulse response model of the channel is given. The core technologies of OFDM are studied, and its basic working principle, system structure model and its important components are discussed. The pilot-assisted wireless channel estimation model in OFDM technology is discussed, and the structure of block, comb and scattered pilot is analyzed. In this paper, four typical channel estimation methods at pilot position are studied, including LSS-MMSE and SVD-LMMSE, and several common interpolation schemes at sub-carriers are introduced. The traditional LMMSE algorithm is studied in detail. In the process of estimating the channel response, the complex matrix must be solved and calculated, and the statistical characteristics of the channel must be known in advance. To solve this problem, the weighted coefficient averaging method is introduced to solve this problem based on the sparse characteristic of channel energy distribution. Based on this, the symbol is processed by joint wavelet, and the experimental simulation is carried out. The results show that, The overall performance of the improved channel estimation model is better than that of the traditional LS algorithm / SVD-LMMSE algorithm and the traditional SVD-LMMSE algorithm, which is only improved by the weighted coefficient averaging method. Although the traditional LMMSE algorithm is simplified, the channel estimation error is large. In this paper, wavelet and empirical mode decomposition are combined to overcome this defect. On the basis of this, threshold threshold is added to deal with the symbol. Finally, the simulation design of the experiment is carried out, and the results show that, The overall performance of the improved channel estimation model is better than that of the traditional LS algorithm and the current popular SVD-LMMSE channel estimation algorithm.
【學(xué)位授予單位】：江西理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN929.53

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