本文選題：時變信道 + 衰落��； 參考：《大連工業(yè)大學》2016年碩士論文

【摘要】：陸地移動無線通信信道具有時變性和衰落特性,其統(tǒng)計特征可以用瑞利分布來描述。但無線信道往往容易受移動端的移動速度、傳輸速率、散射環(huán)境以及載波頻率等因素的影響。而信道是通信系統(tǒng)必不可少的組成部分,信道估計又是移動通信系統(tǒng)的關鍵技術,估計的精度直接影響整個系統(tǒng)的性能。在無線通信技術高速發(fā)展的同時,高速鐵路的發(fā)展速度也令人矚目。高速鐵路運行速度的提升是對無線通信技術的考驗,尤其是對信道估計技術的挑戰(zhàn)。當移動臺移動速度增加的情況下,會產生更大的多普勒頻移,隨之帶來更加惡劣的信道環(huán)境。如何在如此惡劣的環(huán)境中保證通信質量,成為當今無線移動通信領域亟待解決的問題,其關鍵在于信道估計的實現(xiàn)。雖然現(xiàn)有的信道估計方法已經相當成熟,經典的信道估計方法有非盲信道估計、盲信道估計和半盲信道估計,常用的算法包括最小二乘法、最大似然估計、最小均方誤差、迫零算法、線性最小均方誤差、最大比合并等。另外還有很多插值方法,如一階線性插值,二階多項式插值,低通插值,樣條插值,時域插值。但大多估計方法都存在計算量大、復雜度高等問題。因此針對現(xiàn)有信道估計方法存在的問題,本文首先對已有的經典信道估計方法進行分類總結,并對常用的估計算法進行了仿真分析。其次還對無線衰落信道特性進行分析并對衰落信道進行分類總結。之后本文主要在時變條件下,研究移動端移動速度對衰落的影響,利用差分概率的思想提出基于差分概率的信道估計方法。其中重點研究了信道增益的時序關系及其時序差分量的概率統(tǒng)計特性,觀測到信道增益差分量的分布規(guī)律、各時點的差分概率分布是存在的,并且信道增益具有時序依存性。本文還將信道增益的時序關系及其時序差分量的概率統(tǒng)計特性相結合進行仿真實驗,實驗結果表明信道估計的計算量和復雜度得到了降低。最后,還對全文做了總結,得出結論,并對文中所提法下一步可研究的內容及方向做了展望。
[Abstract]:Land mobile wireless communication channels have time-varying and fading characteristics, and their statistical characteristics can be described by Rayleigh distribution. However, wireless channels are often affected by mobile speed, transmission rate, scattering environment and carrier frequency. The channel is an essential part of the communication system, and channel estimation is the key technology of the mobile communication system. The accuracy of the estimation directly affects the performance of the whole system. With the rapid development of wireless communication technology, the development speed of high-speed railway is also remarkable. Improving the speed of high-speed railway is a challenge to wireless communication technology, especially to channel estimation technology. When the moving speed of mobile station increases, the Doppler frequency shift will be larger, and the worse channel environment will follow. How to guarantee the communication quality in such a bad environment has become an urgent problem in the field of wireless mobile communication. The key problem lies in the implementation of channel estimation. Although the existing channel estimation methods are quite mature, the classical channel estimation methods include non-blind channel estimation, blind channel estimation and semi-blind channel estimation. The commonly used algorithms include least square method, maximum likelihood estimation, minimum mean square error. Zero forcing algorithm, linear minimum mean square error, maximum ratio combination, etc. There are also many interpolation methods, such as first order linear interpolation, second order polynomial interpolation, low pass interpolation, spline interpolation, time domain interpolation. However, most of the estimation methods have many problems, such as large computation and high complexity. Therefore, aiming at the problems of existing channel estimation methods, the classical channel estimation methods are classified and summarized in this paper, and the commonly used estimation algorithms are simulated and analyzed. Secondly, the characteristics of wireless fading channel are analyzed and the fading channel is classified and summarized. Then, under the condition of time-varying, the influence of mobile speed on fading is studied, and a channel estimation method based on differential probability is proposed by using the idea of differential probability. The time-series relationship of channel gain and the probability and statistical characteristics of time-series difference components are studied. The distribution law of channel gain difference components is observed. The differential probability distribution of each time point exists and the channel gain is time-dependent. In this paper, the time-series relation of channel gain and the probability and statistical characteristics of time-series difference component are combined to carry out simulation experiments. The experimental results show that the computational complexity and computational complexity of channel estimation are reduced. Finally, the paper summarizes the full text, draws a conclusion, and looks forward to the content and direction that can be studied in the next step.
【學位授予單位】：大連工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：TN929.5

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