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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 闕志達(Tzi-Dar Chiueh) | |
dc.contributor.author | Chien-Yi Wang | en |
dc.contributor.author | 王荐一 | zh_TW |
dc.date.accessioned | 2021-06-15T04:50:28Z | - |
dc.date.available | 2010-08-04 | |
dc.date.copyright | 2010-08-04 | |
dc.date.issued | 2010 | |
dc.date.submitted | 2010-08-02 | |
dc.identifier.citation | [1] Digital Video Broadcasting, http://www.dvb.org/
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Cao, “Channel estimation for OFDM transmission in multipath fading channels based on parametric channel modeling,” IEEE Trans. Commun., vol. 49, no. 3, pp. 467–479, Mar. 2001. [11] C. Cheon and H. L. Bertoni, “Fading of wide band signals associated with displacement of the mobile in urban environments,” in Proc. IEEE VTC Spring, Birmingham, AL, 2002. [12] T. Hwang, C. Yang, G. Wu, S. Li, and G. Y. Li, “OFDM and its wireless applications: a survey,” IEEE Trans. Veh. Technol., vol. 58, no. 4, pp. 1673-1694, May 2009. [13] DVB-T2 Fact Sheet, DVB-T2 - 2nd Generation Terrestrial Broadcasting, Aug. 2008. [14] X. Cai and G. B. Giannakis, “Bounding performance and suppressing intercarrier interference in wireless mobile OFDM,” IEEE Trans. Commun., vol. 51, no. 12, pp. 2047–2056, Dec. 2003. [15] DVB BlueBook A133, Implementation guidelines for a second generation digital terrestrial television broadcasting system (DVB-T2) (draft TR 102 831 V1.1.1), Feb. 2009. 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Hochwald and S. ten Brink, “Achieving near-capacity on a multiple-antenna channel,” IEEE Trans. Commun., vol. 51, no. 3, pp. 389–399, 2003. [39] I. C. Wong and B. L. Evans, “Sinusoidal modeling and adaptive channel prediction in mobile OFDM systems,” IEEE Trans. Signal Process., vol. 56, no. 4, pp. 1601-1615, Apr. 2008. [40] O. Simeone, Y. Bar-Ness, and U. Spagnolini, “Pilot-based channel estimation for OFDM systems by tracking the delay-subspace,” IEEE Trans. Wireless Commun., vol. 3, no. 1, pp. 315-325, Jan. 2004. [41] M. Huang, et al., “Low-complexity subspace tracking based channel estimation method for OFDM systems in time-varying channels,” in Proc. IEEE ICC, Istanbul, 2006, pp. 4618~4623. [42] J. Akhtman and L. Hanzo, “Decision directed channel estimation employing projection approximation subspace tracking,” in Proc. IEEE VTC Spring, Dublin, 2007, pp. 3056~3060. [43] I-W. Lai, et al., “Low-complexity channel-adaptive MIMO detection with just-acceptable error rate channel receivers,” in Proc. IEEE VTC Spring, Barcelona, 2009. [44] D. Zhang, et al., “Informed message update for iterative MIMO demapping and turbo decoding,” in Proc. IEEE ISITA, Taichung, 2010, to appear. | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/45983 | - |
dc.description.abstract | 無線通訊為人類帶來極大便利,日常生活中隨處可見無線技術之應用,如手機、無線上網、數位電視、衛星導航等等。下世代無線通訊系統的研究正如火如荼地進行中,目標是增加傳輸率以及支援高速移動。正交分頻多工(OFDM)是目前最為熱門的調變技術之一,已經被眾多無線傳輸標準採納。OFDM能有效利用頻寬,提供高傳輸率;然而OFDM易受通道快速變化之影響,因而產生之載波間干擾會大幅降低傳輸品質。
在靜態或低速的無線通訊應用中,廣義靜態通道的假設是合理的。然而高速移動時,以往被忽略的通道特性突顯出來,如延遲漂移與路徑生滅。若仍然秉照廣義靜態假設,則設計出來的接收機無法在高速下正常使用。為了使OFDM系統能夠應付日常生活中會遇到的高速移動環境,如高鐵、高速公路,本論文提出一複雜度低且實用性高的演算法,結合通道估計與資料偵測,有效解出訊號。為了證明實用性,本論文採用第二代歐規數位電視地面廣播標準(DVB-T2)驗證提出演算法之效能。搭配DVB-T2採用的低密度奇偶校驗碼(LDPC)進行渦輪解碼(turbo decoding),本論文提出之演算法能夠在高速下成功解出訊號。 | zh_TW |
dc.description.abstract | Wireless communication makes our life much more convenient. In everyday life, we can see applications of wireless technology everywhere, for example, cell phone, WLAN, digital TV, and GPS, etc. The research of wireless communication systems for next generation is going on. The objective is to increase data rate and to support high mobility. Orthogonal frequency-division multiplexing (OFDM) is one of the most popular modulation techniques and already adopted in many wireless standards. OFDM systems utilize bandwidth efficiently and provide high data rate. However, OFDM is vulnerable to rapid channel variation which causes the degradation of transmission quality.
For wireless communication in stationary or low-speed applications, we may assume the wireless channel is wide-sense stationary (WSS). Nevertheless, regarding the receiver design for high-speed applications, some channel characteristics shall not be neglected, say, delay drift and multipath birth/death. If we still make the WSS assumption, such design cannot survive in highly mobile scenarios. In order for OFDM systems to support high mobility in daily life, for example, high-speed trains and vehicles on highway, we propose a low-complexity and practical algorithm which considers channel estimation and data detection jointly. To justify the practicability, we verify our algorithm in a DVB-T2 system. Combined with LDPC, the forward error correction adopted by DVB-T2, to implement the turbo principle, the proposed algorithm is able to detect signals at high mobility successfully. | en |
dc.description.provenance | Made available in DSpace on 2021-06-15T04:50:28Z (GMT). No. of bitstreams: 1 ntu-99-R96943014-1.pdf: 1192535 bytes, checksum: cc223da95e70a699c3ffef9dad66ce9e (MD5) Previous issue date: 2010 | en |
dc.description.tableofcontents | 目錄 I
圖形列表 V 表格列表 VII 第一章 緒論 1 1.1. 行動通訊系統簡介 1 1.2. 研究動機 4 1.3. 論文架構 5 第二章 時變多重路徑衰減通道 7 2.1. 通道衰減之物理現象 7 2.2. 通道衰減之數學模型 9 2.2.1. WSSUS通道 11 2.2.2. Non-WSSUS通道 12 2.2.2.1. 延遲漂移(Delay drift) 13 2.2.2.2. 路徑生滅(Multipath birth/death) 14 2.3. 加成性白色高斯雜訊(AWGN) 14 第三章 正交分頻多工系統與第二代歐規數位電視地面廣播標準 15 3.1. 正交分頻多工調變 16 3.1.1. 類似靜態通道下之正交分頻多工 18 3.1.2. 動態通道下之正交分頻多工 19 3.2. 第二代歐規數位電視地面廣播標準 24 3.3. 系統與模擬環境介紹 27 3.3.1. 考慮延遲漂移之行動通道模型 28 3.3.2. DVB-T2系統參數設定 29 第四章 正交分頻多工系統下之動態通道估計 33 4.1. 二維WIENER濾波器 35 4.2. 基底擴展模型 36 4.2.1. 離散Karhunen–Loève擴展[21] 37 4.2.2. 離散扁長類球體序列[22] 37 4.2.3. 廣義複指數[23] 38 4.2.4. 多項式 39 4.3. 二維基底擴展模型 39 4.3.1. 時間選擇性 39 4.3.2. 頻率選擇性 40 4.3.3. 雙重選擇性 41 4.4. 已知通道統計特性之通道估計 42 4.5. 已知最大都普勒頻率和最大超越延遲之通道估計 43 4.5.1. ML估計 44 4.5.2. SAGE演算法 44 4.6. 基底儲存與帶狀近似 49 4.7. 模擬結果 50 4.7.1. 時間方向之基底擴展模型 50 4.7.2. 頻率方向之基底擴展模型 55 4.7.3. 帶狀近似 57 4.7.4. 提出之估計演算法與LMMSE比較 58 第五章 考慮ICI之資料偵測 61 5.1. 線性等化器 62 5.1.1. 強制歸零(Zero Forcing) 62 5.1.2. 線性最小均方(Linear Minimum Mean Square Error) 63 5.2. 排序漸進干擾消除 63 5.3. 最大可能性序列偵測 65 5.4. 基於SAGE演算法設計之資料偵測 65 5.4.1. 群組間:SAGE演算法應用與分群交替 66 5.4.2. 群組內:樹狀搜尋偵測 69 5.4.3. 硬體實作加速 72 5.5. 模擬結果與比較 73 5.5.1. SAGE收斂情形 74 5.5.2. 群組大小與分群交替對效能的影響 75 5.5.3. 與其他演算法之效能比較 77 第六章 疊代/結合估計與偵測 81 6.1. 疊代LS估計與ICI消除 82 6.2. 疊代LMMSE估計與等化[35] 83 6.2.1. LMMSE渦輪等化[36] 84 6.2.2. LMMSE估計 85 6.2.3. 疊代估計與等化 86 6.3. SAGE演算法應用於結合估計與偵測 86 6.4. 巢狀疊代接收機架構 89 6.5. 模擬結果與比較 89 6.5.1. 不同調變與都普勒頻率下的內接收機效能 91 6.5.2. 與文獻上演算法之效能比較 93 6.5.3. 統計特性誤差對系統效能之影響 95 第七章 結論與展望 97 參考文獻 99 | |
dc.language.iso | zh-TW | |
dc.title | 適用於行動正交分頻多工系統之結合通道估計與資料偵測之巢狀疊代式接收機設計 | zh_TW |
dc.title | Nested Iterative Receiver Design with Joint Estimation and Detection for Mobile OFDM | en |
dc.type | Thesis | |
dc.date.schoolyear | 98-2 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 李學智(Hsueh-Jyh Li),蔡佩芸(Pei-Yun Tsai) | |
dc.subject.keyword | 正交分頻多工,巢狀疊代式接收機,SAGE演算法,結合通道估計與資料偵測,雙重選擇性通道, | zh_TW |
dc.subject.keyword | Orthogonal frequency division multiplexing (OFDM),nested iterative receiver,space-alternating generalized expectation-maximization (SAGE) algorithm,joint estimation and detection (JED),doubly selective channel, | en |
dc.relation.page | 103 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2010-08-02 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 電子工程學研究所 | zh_TW |
顯示於系所單位: | 電子工程學研究所 |
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