本文選題：TD-LTE + PUSCH�。� 參考：《廈門大學(xué)》2014年碩士論文

【摘要】：LTE自2009年商用以來(lái),發(fā)展極為迅速,具有我國(guó)自主知識(shí)產(chǎn)權(quán)的TD-LTE技術(shù),由于其靈活的頻譜配置,也得到了迅速的發(fā)展和廣泛的傳播,2013年底中國(guó)已經(jīng)正式發(fā)放TD-LTE牌照。然而TD-LTE的終端研制還不是很成熟,終端產(chǎn)品的性能需要特定的儀表對(duì)其進(jìn)行測(cè)試,因此TD-LTE測(cè)試儀表的研制及其關(guān)鍵技術(shù)的研究,有助于推動(dòng)整個(gè)行業(yè)的發(fā)展,具有重要意義。 本文首先針對(duì)TD-LTE的PUSCH(Physical Uplink Shared Channel,物理上行共享信道)及其EVM(Error Vector Magnitude,誤差矢量幅度)測(cè)量方法進(jìn)行了研究,EVM屬于無(wú)線指標(biāo)測(cè)試中的調(diào)制質(zhì)量測(cè)試,然后設(shè)計(jì)了PUSCH的EVM的測(cè)量步驟。為了使得測(cè)量結(jié)果達(dá)到預(yù)期目標(biāo),本文對(duì)影響EVM測(cè)量結(jié)果的關(guān)鍵因素進(jìn)行研究與分析,針對(duì)頻率偏移估計(jì)算法、IQ不平衡估計(jì)和補(bǔ)償算法以及信道估計(jì)算法,分別進(jìn)行了算法的性能對(duì)比和分析,并對(duì)相關(guān)的關(guān)鍵算法進(jìn)行研究和優(yōu)化,在頻偏估計(jì)算法中,提出了一種利用對(duì)數(shù)平均計(jì)算頻譜重心的盲估計(jì)算法,該算法性能良好,復(fù)雜度低。在信道估計(jì)算法中,根據(jù)PUSCH中參考信號(hào)幅值恒定的情況,對(duì)MMSE算法進(jìn)行優(yōu)化,降低了算法復(fù)雜度。最后在整體仿真中使用了基于對(duì)數(shù)平均計(jì)算頻譜重心的盲估計(jì)算法和基于PUSCH的MMSE優(yōu)化算法,并求出EVM的測(cè)量值,仿真結(jié)果表明達(dá)到了預(yù)期的目標(biāo)。 未來(lái)本文的進(jìn)一步研究工作是對(duì)影響EVM測(cè)量結(jié)果的其他關(guān)鍵算法如定時(shí)偏移算法、直流估計(jì)算法等進(jìn)行研究,并繼續(xù)優(yōu)化算法的性能,使得EVM的測(cè)量誤差最小化。
[Abstract]:LTE has developed very rapidly since 2009, and the TD-LTE technology with our own intellectual property rights has been developed rapidly and widely spread because of its flexible spectrum configuration. China has officially issued the TD-LTE license at the end of 2013. However, the terminal development of TD-LTE is not very mature, and the performance of the end product needs special instruments to test it. Therefore, the development of TD-LTE test instrument and the research of key technology are helpful to promote the development of the whole industry and have important significance. In this paper, we first study the modulation quality test of TD-LTE (PUSCH(Physical Uplink Shared Channel, physical uplink shared channel) and its EVM(Error Vector magnitude (error vector amplitude) measurement method, and then design the measurement steps of PUSCH EVM. In order to achieve the desired results, this paper studies and analyzes the key factors that affect the EVM measurement results, aiming at the frequency offset estimation algorithm, I. e., the unbalanced IQ estimation and compensation algorithm and the channel estimation algorithm. The performance of the algorithm is compared and analyzed, and the related key algorithms are studied and optimized. In the frequency offset estimation algorithm, a blind estimation algorithm using logarithmic average to calculate the center of spectrum gravity is proposed, which has good performance. Low complexity. In the channel estimation algorithm, the MMSE algorithm is optimized according to the constant amplitude of the reference signal in PUSCH, and the complexity of the algorithm is reduced. Finally, the blind estimation algorithm based on logarithmic average calculation of spectral center of gravity and the MMSE optimization algorithm based on PUSCH are used in the whole simulation, and the measurement value of EVM is obtained. The simulation results show that the desired target is achieved. In the future, the further work of this paper is to study other key algorithms such as timing offset algorithm, DC estimation algorithm and so on, which affect the EVM measurement results, and continue to optimize the performance of the algorithm, so as to minimize the measurement error of EVM.
【學(xué)位授予單位】：廈門大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN929.5

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