標題: | 線性最小均方差通道估計於OFDMA下行傳輸之數位訊號處理器實現 Digital Signal Processor Implementation of LMMSE Channel Estimation for OFDMA Downlink Transmission |
作者: | 蘇映瑄 林大衛 Su, Ying-Xuan Lin, David W. 電子研究所 |
關鍵字: | 通道估計;下行傳輸;正交分頻多址;線性最小均方差;數位訊號處理器;Channel Estimation;Downlink Transmission;OFDMA;LMMSE;DSP |
公開日期: | 2016 |
摘要: | 在本篇論文中,我們根據LTE以及為第五代行動通訊所設計的工業技術研究院(工研院)38 GHz系統規格,討論OFDMA下行通道估計。我們使用MATLAB模擬通道估計,也在數位訊號處理器實現並進行效能分析。
我們採用線性最小均方差的通道估測技術。首先,因其較低的複雜度,使用最小平方差的估測位於導訊(pilot)上的通道頻率響應,然後採用線性內插法來估計在兩導訊中間的通道頻率響應,其次估計延遲參數並利用指數函數的功率延遲曲線求出相關函數,最後根據相關函數做線性最小均方差,估測其他資料載波上的通道頻率響應。上述的流程僅用於LTE系統,但對於工研院系統中,為了在沒有效能損失的情況下有更好的執行效率,我們把線性內插法調整到最後一個步驟使用。在LTE和工研院系統中,我們皆在AWGN通道及多路徑通道上驗證我們的通道估測方法。
在本篇論文中,我們首先介紹LTE及工研院的下行傳輸標準機制,接著描述我們採用的通道估測方法,然後簡介數位訊號處理器的使用環境並最佳化程式,最後在不同傳輸環境下模擬和實作並討論其效能。 In this thesis, we study OFDMA downlink channel estimation based on the LTE system and the Industrial Technology Research Institute (ITRI) system designed for 5G cellular communications operating at 38 GHz. We simulate the channel estimation method with MATLAB and implement on digital signal processor (DSP) to analysis the performance. For the channel estimation method, we first use least-square (LS) estimator on pilot subcarriers because of its low computational complexity. And then we do linear interpolation between two pilot locations in time. After that we estimate the delay parameters and find correlation function with exponential power delay profile (PDP). Finally based on the correlation function, we do linear minimum-mean square error (LMMSE) filtering to estimate the channel frequency responses at other data subcarriers. The above process is used for the LTE system. For the ITRI system, we change the order of linear interpolation to the last step to have more efficient estimation without loss of performance. We verify our channel estimation program in additive white Gaussian noise (AWGN) channel and multipath channel for both LTE and ITRI systems. In this thesis, we first introduce the standard of the LTE and the ITRI downlink transmission. Then we describe the channel estimation method we use. Next, we introduce the DSP implementation environment and optimize the program. Finally, we do the simulation and implementation and discuss the performance in each transmission condition. |
URI: | http://etd.lib.nctu.edu.tw/cdrfb3/record/nctu/#GT070350239 http://hdl.handle.net/11536/139289 |
Appears in Collections: | Thesis |