研究生: |
張家毓 Chang, Chia-Yu |
---|---|
論文名稱: |
正交分頻多工雙向放大轉送中繼系統之時間同步、載波頻率偏移估測與通道估測技術 On Time Synchronization, Carrier Frequency Offset Estimation, and Channel Estimation for OFDM-Based Two-Way Amplify-and-Forward Relay Systems |
指導教授: |
王晉良
Wang, Chin-Liang |
口試委員: |
鐘嘉德
Chung, Char-Dir 歐陽源 Ouyang, Yuan 李志鵬 Li, Chih-Peng |
學位類別: |
碩士 Master |
系所名稱: |
電機資訊學院 - 通訊工程研究所 Communications Engineering |
論文出版年: | 2015 |
畢業學年度: | 103 |
語文別: | 英文 |
論文頁數: | 48 |
中文關鍵詞: | 正交分頻多工 、雙向放大轉送中繼系統 、時間同步 、載波頻率偏移估測 、通道估測 |
外文關鍵詞: | orthogonal frequency-division multiplexing, two-way amplify-and-forward relay systems, time synchronization, carrier frequency offset estimation, channel estimation |
相關次數: | 點閱:3 下載:0 |
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在本篇論文中,我們基於正交分頻多工雙向放大轉送中繼系統提出一種新的前置資料設計,此前置資料中包含兩個訓練符元,用於時間同步、載波頻率偏移估測與通道估測。第一個訓練符元包含一個具有良好特性的特殊複數序列,其序列與自己的共軛複數循環位移做Hadamard乘積會是一個近似完美序列。第二個訓練符元中,我們將兩個不完全Zadoff-Chu序列擺放在頻域交錯的子載波集合上,使此兩個序列在時域及頻域上能彼此區隔。我們將所提出的前置資料用於雙向中繼系統中的其中一個終端點,在相同的前置資料中將第一個訓練符元做適當的循環位移後可用於另一個終端點,藉由第一個訓練符元我們利用自相關與交相關來得到不受載波頻率偏移影響的初步時間同步,接著可以由第二個訓練符元來完成載波頻率偏移估測、精確的時間同步以及通道估測。與現存的相關技術比較下,我們所提出之方法可以得到較好的效能,且不會有太大的運算複雜度增加。
In this thesis, a novel preamble structure of two time-domain training signals is proposed for time synchronization, carrier frequency offset (CFO) estimation, and channel estimation in orthogonal frequency-division multiplexing (OFDM)-based two-way amplify-and-forward (AF) relay systems. The first training signal consists of a specific complex sequence with a nice property that the Hadamard product of the sequence and its complex-conjugate circular-shift version (excluding the zero-shift case) is a near-perfect sequence. The second training signal is a sequence whose frequency-domain counterpart is formed by placing two partial Zadoff-Chu sequences proposed recently on subcarriers in an interleaved manner, where these two sequences are separable in both of the frequency and time domains. Using the proposed preamble for one terminal of the two-way system and a similar preamble with the first training signal circularly shifted appropriately for the other terminal, we can conduct CFO-immune coarse time synchronization for both terminals based on auto-correlation and cross-correlation in the first half of the training period, and then perform CFO estimation, fine time synchronization, and channel estimation in the second half. As compared to existing related works, the proposed approach achieves better performance with a little increase in the computational complexity.
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