本文選題：MIMO-OFDM + 信道估計(jì)��； 參考：《江西理工大學(xué)》2017年碩士論文

【摘要】：現(xiàn)階段隨著各領(lǐng)域技術(shù)的整體發(fā)展,在通訊領(lǐng)域中傳統(tǒng)衡量人們通信質(zhì)量的標(biāo)準(zhǔn)已不再適用,現(xiàn)代通信正在朝著高質(zhì)量、高速率的方向發(fā)展。在這種飛速發(fā)展的大環(huán)境下,必須對(duì)傳統(tǒng)的通信技術(shù)進(jìn)行突破,在傳統(tǒng)技術(shù)的基礎(chǔ)上進(jìn)行改進(jìn)或者尋找新的滿足現(xiàn)階段通信的關(guān)鍵技術(shù)。以MIMO-OFDM系統(tǒng)為框架的現(xiàn)代通信系統(tǒng),通過(guò)使用天線的多收多發(fā)技術(shù),使該系統(tǒng)具有諸多優(yōu)點(diǎn),能夠滿足現(xiàn)階段高質(zhì)量、高速率的通信傳輸標(biāo)準(zhǔn)。但是在實(shí)際信號(hào)傳輸過(guò)程中信號(hào)會(huì)受到周圍環(huán)境以及障礙物的影響,產(chǎn)生不同程度的衰落和時(shí)延,造成符號(hào)間的干擾,影響信號(hào)的傳輸質(zhì)量。本文圍繞MIMO-OFDM系統(tǒng)為框架,采用全新的壓縮采樣技術(shù)對(duì)稀疏多徑信道進(jìn)行研究。以達(dá)到獲取更加精確的CSI,提升通信傳輸質(zhì)量和速率的目的。本文主要完成的工作有:(1)對(duì)MIMO-OFDM系統(tǒng)模型展開(kāi)研究,在討論了其系統(tǒng)模型和基本原理的基礎(chǔ)上,并研究了信道的衰落特性和導(dǎo)頻結(jié)構(gòu)。為了克服衰落特性對(duì)傳輸?shù)挠绊?對(duì)基于導(dǎo)頻的LS、MMSE和基于DFT的算法進(jìn)行分析研究,并在MIMO-OFDM系統(tǒng)中對(duì)這幾種算法進(jìn)行仿真,分析其優(yōu)缺點(diǎn)。(2)對(duì)多用戶信道估計(jì)進(jìn)行了研究分析,總結(jié)了多用戶MIMO-OFDM系統(tǒng)中的編碼和波束賦型技術(shù),并對(duì)其信道容量進(jìn)行分析。由于多用戶在獲取信道狀態(tài)信息時(shí)存在用戶間的干擾問(wèn)題,系統(tǒng)獲取的信道狀態(tài)信息是不完整的,本文在MMSE算法的基礎(chǔ)上利用信道的時(shí)延包絡(luò)特性對(duì)信道狀態(tài)信息進(jìn)行進(jìn)一步的精確。仿真表明改進(jìn)后的算法在對(duì)多用戶MIMO-OFDM系統(tǒng)的信道估計(jì)在精確度上有所提高。(3)理論分析和實(shí)測(cè)表明信道具有稀疏特性,針對(duì)信道的這種特性,對(duì)基于CS理論的貪婪算法進(jìn)行信道估計(jì)研究。重點(diǎn)討論了基于壓縮感知的幾種貪婪算法:OMP、ROMP及SP算法,并給出了實(shí)驗(yàn)仿真比較。同時(shí)根據(jù)壓縮感知算法的稀疏度和復(fù)雜度問(wèn)題,本文在對(duì)CoSaMP算法進(jìn)行研究的基礎(chǔ)上,根據(jù)原子弱選擇標(biāo)準(zhǔn)對(duì)CoSaMP算法進(jìn)行改進(jìn),提出了基于閾值改進(jìn)的CoSaMP算法,仿真表明改進(jìn)后的算法提高了算法的速率。
[Abstract]:At present, with the overall development of various fields of technology, the traditional standard of measuring people's communication quality is no longer applicable in the field of communication, and modern communication is developing towards the direction of high quality and high speed.In this environment of rapid development, we must break through the traditional communication technology, improve on the basis of the traditional technology or find new key technologies to meet the current stage of communication.The modern communication system based on MIMO-OFDM system has many advantages by using the technique of multiple antennas, which can meet the communication standards of high quality and high speed at the present stage.However, in the actual signal transmission process, the signal will be affected by the surrounding environment and obstacles, resulting in varying degrees of fading and delay, causing inter-symbol interference, and affecting the quality of signal transmission.In this paper, a novel compressed sampling technique is used to study sparse multipath channel around MIMO-OFDM system.In order to achieve more accurate CSI, improve the quality and rate of communication transmission.The main work of this paper is to study the MIMO-OFDM system model. Based on the discussion of the system model and the basic principle, the fading characteristics and pilot structure of the channel are studied.In order to overcome the influence of fading characteristics on transmission, the algorithms based on pilot frequency and DFT are analyzed and simulated in MIMO-OFDM system. The advantages and disadvantages of these algorithms are analyzed.The coding and beamforming techniques in multiuser MIMO-OFDM systems are summarized, and the channel capacity is analyzed.The channel state information obtained by the system is incomplete because of the interference between the users when the multi-user acquires the channel state information.Based on the MMSE algorithm, the channel state information is further accurate by using the time-delay envelope of the channel.Simulation results show that the improved algorithm improves the accuracy of channel estimation for multi-user MIMO-OFDM systems. The theoretical analysis and experimental results show that the channel has sparse characteristics.The greedy algorithm based on CS theory is studied for channel estimation.This paper mainly discusses several greedy algorithms based on compression perception: OMP ROMP and SP algorithms, and gives the experimental simulation comparison.At the same time, according to the problem of sparse degree and complexity of compressed sensing algorithm, based on the research of CoSaMP algorithm, this paper improves the CoSaMP algorithm according to the atomic weak selection criterion, and proposes an improved CoSaMP algorithm based on threshold.Simulation results show that the improved algorithm improves the speed of the 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)】：TN919.3

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