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博碩士論文 etd-0824107-160815 詳細資訊
Title page for etd-0824107-160815
論文名稱
Title
正交分頻多工調變系統中時間同步的估測方法
A Novel Timing Estimation Method for OFDM Systems
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
53
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2007-07-30
繳交日期
Date of Submission
2007-08-24
關鍵字
Keywords
時間偏移估測
Timing offset estimation
統計
Statistics
本論文已被瀏覽 5660 次,被下載 2250
The thesis/dissertation has been browsed 5660 times, has been downloaded 2250 times.
中文摘要
本論文的主要目的,是在正交分頻多工(Orthogonal Frequency Division Multiplexing, OFDM)系統之中,提出一個新的訓練符元架構,並在此架構之下,得到一個新的時間偏移估測器,以改善傳統時間估測器的缺點,並增進時間估測的準確度。在正交分頻多工系統中,傳統的時間估測方法主要是由Schmidl所提出[4,5],但是此架構的時間估測器之時間公制條件(Timing Metric)會有平台效應,造成時間估測極大的誤差。本論文所提出之方法,將藉由電腦模擬來驗證其效能,主要是比較各個時間估測器的均方誤差(Mean Square Error, MSE)。電腦模擬證明,本論文所提出之方法,除了改善傳統Schmidl所提出之架構,降低平台效應的影響,也比Minn [9]及Park [10]所提出之方法更優越。
Abstract
In this thesis, a novel training sequence is proposed for timing offset estimation in orthogonal frequency division multiplexing (OFDM) systems. The proposed training sequence and the derived timing offset estimator are proved to outperform traditional schemes. In timing estimation of OFDM systems, the scheme proposed by Schmidl [4,5] is perhaps the most well-known one. However, Schmidl’s scheme has a plateau in timing metric, which substantially degrades system performance. In this thesis, simulation experiments are conducted to evaluate the performance of the proposed timing offset estimator and the mean square error (MSE) is adopted as the performance measure. Simulation results demonstrate that the performance of the proposed scheme not only improves Schmidl’s scheme, but also outperforms Minn’s [9] and Park’s [10] schemes.
目次 Table of Contents
致謝 Ⅱ
中文摘要 III
ABSTRACT Ⅳ
目錄 Ⅴ
圖目錄 VII
第一章 緒論 1
1.1 前言 1
1.2 研究動機 2
1.3內容大綱 3
第二章 OFDM調變介紹、系統架構及特性 4
2.1 正交分頻多工系統介紹 4
2.2正交分頻多工系統架構 6
2.3保護區間(GUARD INTERVAL, GI)與循環字首(CYCLIC PREFIX, CP) 13
2.4正交分頻多工系統的優缺點 16
第三章 同步基本原理及傳統方法 17
3.1同步的基本概念 17
3.2同步的系統模型 18
3.3正交分頻多工之時間偏移的估測方法 19
3.3.1 SCHMIDL’S方法 19
3.3.2 MINN’S方法 20
3.3.3 PARK’S方法 21
第四章 提出新的同步架構及數學分析 23
4.1反高斯分佈(INVERSE GAUSSIAN DISTRIBUTION) 23
4.2提出新的架構及時間公制(TIMING METRIC) 24
4.3時間公制在正確時間點的統計特性分析 27
4.3.1期望值之推導 27
4.3.2變異數之推導 32
第五章 電腦模擬結果 38
第六章 結論 42
參考文獻 43
參考文獻 References
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