【摘要】：模擬通信系統(tǒng)到數(shù)字通信系統(tǒng)的發(fā)展是移動(dòng)通信領(lǐng)域的重大轉(zhuǎn)變,隨著人們對(duì)高速率、大容量數(shù)據(jù)傳輸?shù)男枨?通信傳輸技術(shù)也在不斷發(fā)展。正交頻分復(fù)用(OFDM)技術(shù)有效地提高了信道利用率,多輸入多輸出(MIMO)技術(shù)充分利用空間資源,提高信道容量。但是,在實(shí)際信道中,OFDM技術(shù)對(duì)無(wú)線通信系統(tǒng)的時(shí)偏和頻偏都異常地敏感,尤其MIMO技術(shù)的應(yīng)用將增加這種問(wèn)題的嚴(yán)重性。若系統(tǒng)接收端接收到精準(zhǔn)的無(wú)線信道特征可以減少失真,所以信道估計(jì)技術(shù)尤為重要。針對(duì)現(xiàn)實(shí)傳輸信號(hào)系統(tǒng)存在的一些問(wèn)題,本課題先對(duì)傳統(tǒng)的基于導(dǎo)頻估計(jì)算法進(jìn)行研究,再對(duì)基于壓縮感知(CS)的估計(jì)算法進(jìn)行研究。主要的研究工作和創(chuàng)新性的研究成果如下:(1)基于離散傅里葉變換(DFT)的OFDM信道估計(jì)研究。針對(duì)DFT僅改善CP外的樣本點(diǎn)噪聲,沒(méi)有考慮到CP內(nèi)噪聲的問(wèn)題,采用一種新的改進(jìn)閾值的估計(jì)算法。該算法的思想是首先對(duì)CP內(nèi)樣本點(diǎn)的能量取其平均值,然后對(duì)CP外樣本點(diǎn)能量升序后取合適區(qū)間上的能量的均值,再取兩者之和作為本文的閾值。仿真結(jié)果證明了本文采用的新閾值方法有效地提高了系統(tǒng)估計(jì)性能。(2)對(duì)于CS重構(gòu)算法的MIMO-OFDM系統(tǒng)信道估計(jì)研究。針對(duì)傳統(tǒng)的信道估計(jì)算法若要達(dá)到精確度較高的信道特征,需要大量導(dǎo)頻,導(dǎo)致頻譜利用率低、導(dǎo)頻污染嚴(yán)重的問(wèn)題,利用MIMO-OFDM系統(tǒng)的時(shí)域上的稀疏特性,采用CS重構(gòu)信號(hào)方法對(duì)MIMO-OFDM系統(tǒng)進(jìn)行性能估計(jì),仿真結(jié)果表明在獲得相同的精確性性能時(shí),采用CS重構(gòu)信號(hào)方法需要的導(dǎo)頻數(shù)遠(yuǎn)遠(yuǎn)少于采用傳統(tǒng)導(dǎo)頻參數(shù)的估計(jì)方法。(3)對(duì)于梯度追蹤(GP)的MIMO-OFDM稀疏信道估計(jì)方法研究。針對(duì)正交匹配追蹤及其改進(jìn)算法在處理大規(guī)模數(shù)據(jù)時(shí),由于需要處理大量最小二乘計(jì)算,導(dǎo)致計(jì)算復(fù)雜度較高的問(wèn)題,采用梯度追蹤重構(gòu)方法對(duì)MIMO-OFDM系統(tǒng)進(jìn)行信道性能估計(jì)。該算法采用梯度思想選擇原子,避免計(jì)算最小二乘,在保證信道的估計(jì)準(zhǔn)確性同時(shí)能減少計(jì)算復(fù)雜度,從而提高系統(tǒng)估計(jì)性能。仿真結(jié)果表明基于GP方法的估計(jì)運(yùn)算復(fù)雜度比OMP方法有所降低。
[Abstract]:The development of analog communication system to digital communication system is a great change in the field of mobile communication. With the demand of high speed and large capacity data transmission, communication transmission technology is also developing. Orthogonal frequency division multiplexing (OFDM) technology can effectively improve channel utilization. Multi-input and multi-output (MIMO) technology makes full use of space resources and improves channel capacity. However, in the actual channel, the OFDM technology is very sensitive to both the time offset and the frequency offset of the wireless communication system, especially the application of MIMO technology will increase the severity of this problem. If the receiver receives accurate wireless channel features, the distortion can be reduced, so channel estimation is particularly important. Aiming at some problems existing in the real transmission signal system, this paper first studies the traditional pilot estimation algorithm, and then studies the compressed perceptual (CS) estimation algorithm. The main research work and innovative research results are as follows: (1) OFDM channel estimation based on discrete Fourier transform (DFT). Aiming at the problem that DFT only improves the noise of sample points outside CP and does not take into account the noise in CP, a new improved threshold estimation algorithm is proposed. The idea of this algorithm is to take the mean of the energy of the sample points in CP first, then to take the mean value of the energy of the appropriate interval after the ascending order of the energy of the sample points outside the CP, and then to take the sum of the two as the threshold of this paper. Simulation results show that the new threshold method proposed in this paper can effectively improve the performance of system estimation. (2) the channel estimation of MIMO-OFDM system based on CS reconstruction algorithm is studied. In order to achieve the channel characteristics with high accuracy, the traditional channel estimation algorithm needs a large number of pilots, which leads to low spectral efficiency and serious pilot pollution. Therefore, the sparse characteristic of MIMO-OFDM system in time domain is utilized. The CS reconstruction signal method is used to estimate the performance of MIMO-OFDM system. The simulation results show that the same accuracy performance is obtained. The number of pilots needed to reconstruct the signal by CS is much less than that by using the traditional pilot parameter estimation method. (3) the MIMO-OFDM sparse channel estimation method with gradient tracking (GP) is studied. In order to solve the problem of high computational complexity caused by the need to deal with a large number of least square calculations when dealing with large scale data, gradient tracking reconstruction method is used to estimate the channel performance of MIMO-OFDM systems. The algorithm adopts gradient method to select atoms and avoids the calculation of least squares. It can reduce the computational complexity while ensuring the accuracy of channel estimation and thus improves the performance of system estimation. Simulation results show that the estimated computational complexity based on GP method is lower than that of OMP method.
【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)】：TN919.3;TN929.53

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 王強(qiáng);張培林;王懷光;楊望燦;陳彥龍;;壓縮感知中測(cè)量矩陣構(gòu)造綜述[J];計(jì)算機(jī)應(yīng)用;2017年01期

2 王輝;王斌;;多徑衰落信道下基于循環(huán)累積量的調(diào)制分類算法[J];信號(hào)處理;2016年10期

3 仲偉志;蘇生;劉鑫;井慶豐;;基于循環(huán)前綴的MIMO-OFDM改進(jìn)信道估計(jì)算法[J];系統(tǒng)工程與電子技術(shù);2017年01期

4 丁遠(yuǎn)晴;;基于壓縮感知的MIMO OFDM系統(tǒng)稀疏信道估計(jì)[J];通信技術(shù);2016年10期

5 王志文;徐以濤;黃鑫權(quán);趙勇;林剛;;基于觀測(cè)矩陣優(yōu)化的自適應(yīng)壓縮寬帶頻譜感知[J];通信技術(shù);2016年01期

6 任曉奎;葛君;孫興海;;基于壓縮感知改進(jìn)算法的MIMO-OFDM稀疏信道估計(jì)[J];計(jì)算機(jī)工程與應(yīng)用;2016年17期

7 樊蓉;慕福奇;蘇明月;;OFDM系統(tǒng)基于導(dǎo)頻的DFT信道估計(jì)改進(jìn)算法[J];南京郵電大學(xué)學(xué)報(bào)(自然科學(xué)版);2015年02期

8 崔磊;王慧瑩;;第五代移動(dòng)通信關(guān)鍵技術(shù)研究[J];黑龍江科學(xué);2015年02期

9 練柱先;余江;徐麗敏;肖文珂;劉言立;夏鍇;;一種快速的LMMSE多徑信道估計(jì)算法[J];中南大學(xué)學(xué)報(bào)(自然科學(xué)版);2014年12期

10 劉盼盼;李雷;王浩宇;;壓縮感知中基于變尺度法的貪婪重構(gòu)算法的研究[J];通信學(xué)報(bào);2014年12期

相關(guān)博士學(xué)位論文 前1條

1 田園;分布式MIMO OFDM系統(tǒng)同步技術(shù)研究[D];電子科技大學(xué);2011年

相關(guān)碩士學(xué)位論文 前1條

1 黃茜茜;LTE下行鏈路的信道估計(jì)算法研究[D];江西理工大學(xué);2016年

，

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