基於子空間追蹤之IEEE 802.11p通道估計

Abstract

在本篇論文中，我們根據電機電子工程師學會(IEEE)為車用網路制定的標準IEEE 802.11p，討論子空間追蹤(subspace-tracking)下行通道估計在IEEE 802.11p系統下的效能。並且使用MATLAB進行通道估計之模擬。 我們將子空間追蹤通道估計法應用在導頻(pilot)子載波的最小平方估計上，藉此增加通道估計的精度，再將導頻子載波的通道估計結果內差，得到對應符號(symbol)的通道估計。在子空間追蹤通道估計法中，我們將通道頻率響應參數化成延遲矩陣(delay matrix)以及振幅向量(amplitude vector)的乘積。由於這兩種參數有不同的時變特性，因此我們分別使用子空間追蹤以及最小均方法來估測兩者。我們利用加性高斯白雜訊 (AWGN) 通道以及瑞雷衰落通道(Rayleigh fading channel)來驗證此方法在IEEE 802.11p系統下的效能。 在本篇論文中，我們首先介紹IEEE 802.11p的系統架構以及車用網路的應用情境，接著描述我們採用的通道估測方法，然後簡介目前常見的通道估計方法，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 downlink channel estimation based on the IEEE 802.11p system designed for vehicular communications. We investigate the performance of subspace-tracking channel estimation method in a IEEE 802.11p downlink system. And we simulate the channel estimation method with MATLAB. We use subspace-tracking channel estimation method as an intermediate step after obtaining the least-squares (LS) estimate over the pilot subcarriers, whose purpose is to increase the accuracy of the estimate over the pilot subcarriers. And this preliminary estimate is interpolated/smoothed over the entire frequency-time grid to obtain the channel estimate of the corresponding symbol. In subspace-tracking channel estimator, we parameterize the channel frequency response into the multiplication of delay matrix and amplitude vector. Since the temporal variation characteristic of these two parameters are different, we use subspace-tracking and least mean square (LMS) methods to estimate them respectively. We show the performance of subspace-tracking estimator in additive white Gaussian noise (AWGN) channel and Rayleigh fading channel for IEEE 802.11p system. In this thesis, we first introduce the system structure of IEEE 802.11p standard. Then we describe the channel estimation method we use. Next, we introduce the common channel estimators for IEEE 802.11p system. Finally, we do the simulation and discuss the performance in each transmission condition.