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研究生：	林子平 Lin, Tzu-Ping
論文名稱：	頻率選擇性衰退通道中的盲閉式OFDM信號偵測 Blind Detection of OFDM Signals in Frequency-Selective Fading Channels
指導教授：	張名先 Chang, Ming-Xian
學位類別：	碩士 Master
系所名稱：	電機資訊學院 - 電腦與通信工程研究所 Institute of Computer & Communication Engineering
論文出版年：	2010
畢業學年度：	98
語文別：	英文
論文頁數：	45
中文關鍵詞：	通道估測、通道脈衝響應、盲閉式偵測、正交分頻多工系統
外文關鍵詞：	estimation, channel impulse response, blind detection, OFDM
相關次數：	點閱：109 下載：3
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在無線通訊環境中，使用正交分頻多工系統(OFDM)，能有效於多路徑的環境下與低複雜度的頻域等化。為了達到更高的通道使用率，我們使用盲閉式來取代原有的引導訊號於OFDM 訊號偵測，以提高資料的運載量，進而增加通道使用率。故盲閉式能使傳輸量上升。
本篇論文我們提出盲閉式訊號檢估的演算法於 OFDM 系統下，代替原有的多項式來模擬子頻道的通道響應(CR)變化[11]，我們改用通道脈衝響應來模擬(CSI)。配合使用branch-and-bound 原理來解決非線性的整數規劃問題，並使用遞迴計算如[11]。
更進一步探討降低複雜度，我們使用深度優先搜尋來降低拜訪點數。並使用多項式於每個子通道的時變通道響應，使得於branch-and-bound 演算法的起始值，利用預先估計的通道響應來找尋較佳的起始資料串。模擬結果證明CIR 效果能優於[11]，且能有效的降低複雜度。

For wireless communications, the orthogonal frequency division multiplexing (OFDM) system is frequently applied due to its robustness to the multipath environment and its low-complexity frequency-domain equalization. In order to achieve higher channel rate of utilization, we can use the blind method instead of the pilot-based method for the signal detection in OFDM systems. The blind approach also increases the data throughput.
In this thesis, we propose a Blind signal detection algorithm for the OFDM system. Instead of using a polynomial to model the channel response (CR) variation across sub-channels [11], we consider the model of channel impulse response (CIR). Then we apply the branch-and-bound principle to solve the non-linear integer programming problem, with a recursive computation as that in [11].
To further reduce the complexity, we use the depth-first searching order to reduce the number of visiting nodes. We also model the time-variation of CRs in each sub-channel as a polynomial, and use the predicted CRs to obtain a better initial data sequence in the branch-and-bound algorithm. The simulation results show that the CIR model leads to better performance than [11], and the complexity reduction approaches are effect.

中文摘要.................................................I
Abstract................................................II
List of Figures.........................................VI
Chapter 1................................................1
Introduction.............................................1
Chapter 2................................................3
System and Channel Model.................................3
2.1 System Model.........................................3
2.2 Channel Model........................................5
2.2.1 Modification of Jake’s Rayleigh Fading Model......5
Chapter 3................................................8
Blind Detection..........................................8
3.1 Polynomial Model.....................................8
3.2 CIR Model...........................................12
3.3 Blind Detection.....................................15
3.3.1 Integer Programming...............................15
3.3.2 Branch-and-Bound Algorithm........................17
3.3.3 Recursive formula.................................22
3.4 Simulation Results..................................25
Chapter 4...............................................27
Blind and Semi-Blind Detection..........................27
4.1 Semi-Blind Base Method..............................27
Chapter 5...............................................30
Complexity Reducing Method..............................30
5.1 Motive..............................................30
5.2 Channel Prediction by Curve Fitting.................31
5.3 Searching Method....................................36
5.3.1 Depth-First with Sibling Memory...................36
5.3.2 Breadth-First with Sibling Memory.................38
5.4 Simulation Results..................................40
Chapter 6...............................................43
Conclusion..............................................43
Chapter 7...............................................44
Bibliography............................................44
                                    

[1] W. Y. Zou and Y. Wu, “COFDM: an overview,” IEEE Trans. Broadcast., vol. 41, pp.1-8, Mar. 1995.
[2] ETSI ETS 300 401 ed.1 (1995-02). Digital audio broadcasting (DAB); DAB to mobile, portable and fixed receivers. ETSI. 1995.
[3] ETSI EN 300 744 V1.1.2 (1997-08): Digital broadcasting systems for television, sound and data services; framing structure, channel coding and modulation for digital terrestrial television. ETSI, 1997.
[4] W. G. Jeon, K. H. Chang and Y. S. Cho, “An Equalization Technique for Orthogonal Frequency-Division Multiplexing Systems in Time-Variant Multipath Channels,” IEEE Trans. Commun. vol. 47, pp.27-32, Jan. 1999.
[5] Y. Li, and X. Huang, “The Simulation of Independent Rayleigh Faders,” IEEE Trans. Commun., vol. 50, NO. 9, pp. 1503-1514, Sept. 2002.
[6] M. X. Chang and Y. T. Su, “2-D regression channel estimation for equalizing OFDM signals,” Proc IEEE 51th Vehicular Technology Conference, Tokyo, pp. 240-244, May 2000.
[7] M. X. Chang and Y. T. Su, “Model-based channel estimation for equalizing OFDM signal,” IEEE Trans. Commun., vol. 50, pp. 240-544, Apr. 2002.
[8] M. X. Chang and Y. T. Su, “Performance Analysis of Equalized OFDM System in Rayleigh Fading,” IEEE Trans. Commun., vol. 1, NO. 4, October 2002.
[9] M. Russell and G. L. Stüber, “Interchannel interference analysis of OFDM in a mobile environment,” in Proc. IEEE VTC’95, Chicago, IL, July 1995, pp. 820-824.
[10] G. Strang, Linear Algebra and Its Applications, 3rd ed. Philadelphia, PA: Saunders, 1988.
[11] Ming-Xian Chang and Yu T. Su, “Blind and Semiblind Detections of OFDM Signals in Fading Channels” IEEE Trans. Commun., VOL. 52, NO. 5, MAY 2004.

校內：2020-12-25公開
校外：2020-12-25公開

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