發(fā)布時(shí)間：2018-06-02 12:35

  本文選題：時(shí)分雙工 + 探測(cè)參考信號(hào)��； 參考：《西安電子科技大學(xué)》2015年碩士論文

【摘要】：LTE系統(tǒng)中通過(guò)鏈路自適應(yīng)可以有效的提高數(shù)據(jù)速率和頻譜效率,在上行鏈路數(shù)據(jù)傳輸中作為提升吞吐量的手段,該項(xiàng)技術(shù)尤為重要。自適應(yīng)技術(shù)中有兩個(gè)關(guān)鍵研究點(diǎn):測(cè)量和預(yù)測(cè)。目的是為了隨信道、干擾等環(huán)境的變化及時(shí)調(diào)整數(shù)據(jù)發(fā)送設(shè)定的參數(shù),實(shí)現(xiàn)頻譜利用率和誤塊率之間的最佳平衡。本文針對(duì)直接與最終反饋給用戶的調(diào)制編碼方式相關(guān)聯(lián)的信干噪比入手,探討了時(shí)分雙工上行鏈路中干擾測(cè)量和信干噪比預(yù)測(cè)的問(wèn)題,并給出了理論闡述和計(jì)算機(jī)仿真分析對(duì)比。首先,本文給出了LTE協(xié)議中關(guān)于時(shí)分雙工幀結(jié)構(gòu)配置和探測(cè)參考信號(hào)相關(guān)內(nèi)容,為后文研究提供了參考標(biāo)準(zhǔn)。探測(cè)參考信號(hào)分為周期和非周期探測(cè),本文主要采用周期探測(cè)。在小區(qū)建模使用華為軟頻率復(fù)用方案,降低相鄰小區(qū)邊緣用戶間的同頻干擾。對(duì)于探測(cè)參考信號(hào)的傳輸,靈活的采用時(shí)分復(fù)用、頻分復(fù)用和碼分復(fù)用相結(jié)合的方式,形成了一種特定幀結(jié)構(gòu)下的干擾測(cè)量方案,在較短的時(shí)間內(nèi)獲得干擾信息并可以進(jìn)行及時(shí)的更新。然后在基于探測(cè)參考信號(hào)的信道估計(jì)常用算法中選擇一種性能較好的方法,即循環(huán)移位時(shí)域信道估計(jì)法,因其對(duì)于多用戶敏感性較共軛相消信道估計(jì)法低。再將該方法結(jié)合MMSE信道估計(jì)使用,構(gòu)成一種在全頻帶下保證估計(jì)性能的算法,歸一化的MSE達(dá)到了0.1,能夠有效的得到所需干擾功率信息,測(cè)量出較為準(zhǔn)確的信干噪比。雖然反饋調(diào)制編碼方式時(shí)根據(jù)的是最近的信干噪比信息,但是在傳輸過(guò)程中會(huì)有一定的時(shí)延。在時(shí)延的時(shí)間段中,信道和干擾傳輸背景環(huán)境均發(fā)生了變化,并不能準(zhǔn)確的反映用戶下一時(shí)刻發(fā)送數(shù)據(jù)時(shí)應(yīng)當(dāng)采用的調(diào)制階數(shù)和碼率,所以需要對(duì)信干噪比進(jìn)行預(yù)測(cè)。預(yù)測(cè)方法主要分為線性預(yù)測(cè)方法和非線性預(yù)測(cè)方法,非線性預(yù)測(cè)方法復(fù)雜度高,需要調(diào)整的參數(shù)更多,更偏向于實(shí)際經(jīng)驗(yàn)來(lái)選取參數(shù)。線性方法簡(jiǎn)單有效,但對(duì)于非線性的數(shù)據(jù)抖動(dòng)處理并不一定如非線性方法優(yōu)越。最后,在搭建的系統(tǒng)模型下進(jìn)行了各類預(yù)測(cè)方法的仿真,實(shí)現(xiàn)吞吐量性能提升。
[Abstract]:The data rate and spectral efficiency can be improved effectively by link adaptation in LTE system. This technique is especially important in uplink data transmission as a means to enhance throughput. There are two key research points in adaptive technology: measurement and prediction. The aim of this paper is to adjust the parameters of data transmission and achieve the best balance between spectrum efficiency and block error rate with the change of channel, interference and other environments. In this paper, the problem of interference measurement and signal-to-noise ratio prediction in time division duplex uplink is discussed. The theoretical explanation and computer simulation analysis are also given. First of all, this paper gives the related contents of the LTE protocol about the time division duplex frame configuration and the detection reference signal, which provides the reference standard for the later research. The reference signal is divided into periodic detection and aperiodic detection. Huawei soft frequency reuse scheme is used in cell modeling to reduce the same frequency interference between adjacent cell edge users. For the transmission of probe reference signal, the method of time division multiplexing, frequency division multiplexing and code division multiplexing is used flexibly to form an interference measurement scheme under a specific frame structure. Access to interference information in a short time and can be updated in a timely manner. Then, one of the common channel estimation algorithms based on probe reference signal is the cyclic shift time-domain channel estimation method, which is less sensitive to multi-user than conjugate cancellation channel estimation method. Then the method is combined with MMSE channel estimation to form an algorithm to ensure the estimation performance in full frequency band. The normalized MSE reaches 0.1, which can effectively obtain the required interference power information and measure the more accurate signal-to-interference noise ratio. Although the feedback modulation coding method is based on the latest signal-to-noise ratio information, there will be a certain delay in the transmission process. In the time delay, both the channel and the interference transmission background environment have changed, which can not accurately reflect the modulation order and the bit rate that the user should adopt when transmitting data at the next time, so it is necessary to predict the signal-to-noise ratio. The prediction method is mainly divided into linear prediction method and nonlinear prediction method. The nonlinear prediction method has a high complexity, more parameters need to be adjusted, and it is more inclined to choose the parameters from practical experience. The linear method is simple and effective, but the nonlinear data jitter processing is not always superior to the nonlinear method. Finally, various prediction methods are simulated under the system model to improve throughput performance.
【學(xué)位授予單位】：西安電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TN929.5

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本文編號(hào)：1968785