博碩士論文 945203003 詳細資訊




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姓名 鄭乾君(Chien-Chun Cheng)  查詢紙本館藏   畢業系所 通訊工程學系
論文名稱 適用於移動式正交分頻多工通訊系統的改良型時域通道響應追蹤演算法
(Improved Time-Domain Channel Tracking Algorithms for Mobile OFDM Communications)
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摘要(中) 為了應付行動正交分頻多工通訊系統的通道估計問題,系統中常常需要插入許多領航訊號 (pilots) 因而降低頻寬使用效率。為節省所使用的領航訊號,本論文研究在時變通道環境下,利用決策回授機制(Decision-Feedback),提出改良的最小平方法 (LS) 時域通道響應估測器。然而,決策回授系統的缺點為決策錯誤累積(Decision-error propagation),我們提出錯誤檢測器來偵測決策錯誤,並且提出補償方法來避免決策錯誤累積。在實驗模擬的結果中,我們比較所提出不同的檢測器與通道估計補償方法的性能,在時變通道下得到可以接受的位元錯誤率,並且在追蹤的過程中不需要任何領航訊號,大幅減少系統傳輸效率的損失。
摘要(英) To deal with the channel estimation problem, the mobile orthogonal frequency division multiplexing (OFDM) system usually requires pilots to be inserted in transmitted signals in which the bandwidth efficiency is reduced. For the purpose of saving pilots, this paper studies a new least squares (LS) time-domain channel estimator using a decision-feedback loop. However, the drawback of the decision-feedback system is decision-error propagation. We propose error detectors for reducing the error probability and some compensation methods for enhancing channel estimation. In simulation results, the performances of the proposed decision-error detectors and compensation methods are compared. We show that the acceptable bit error rate can be achieved without pilots used for channel tracking and thus, the loss of bandwidth efficiency due to pilots is significantly reduced.
關鍵字(中) ★ 決策回授
★ 通道追蹤
關鍵字(英) ★ Wimax Downlink
★ Decision Feedback
論文目次 Chapter 1 1
1.1 Overview 1
1.2. Introduction of WiMax 3
1.2.1 What is WiMax 3
1.2.2 802.16-2004 and 802.16e WiMAX networks 4
1.2.3 Air interface nomenclature and PHY compliance 5
1.2.4 OFDM symbol parameters 6
1.3. Introduction of OFDM 9
1.3.1. General concept of OFDM 9
1.3.2 Preamble architecture 10
1.3.3 Pilots architecture 11
1.4 Introduction of the channel model 13
1.4.1 Gaussian noise 13
1.4.2 Channel impulse model 13
1.4.3 Power-Delay profile model 15
Chapter 2 18
2.1 Formulation of the OFDM system 18
Chapter 3 21
3.1 The Decision Feedback Device 21
3.1.1 Observation 21
3.1.2 Motivation 22
3.1.3 Proposed Solution 23
3.2 The Smoothing Device 25
3.2.1 Observation 25
3.2.2 Motivation 25
3.2.3 Proposed Solution 26
3.2.4 Optimum smoothing factors 27
3.3 The Time-Domain Channel Estimator 28
3.3.1 Observation 28
3.3.2 Motivation 29
3.3.3 Proposed Solution 29
3.3.4 Simplified Solution 34
3.4 The Error Detector 35
3.4.1 Observation 35
3.4.2 Motivation 35
3.4.3 Proposed Solution 36
3.5 Error Compensation 41
3.5.1 Observation 41
3.5.2 Motivation 42
3.5.3 Proposed Solution 43
3.6 Iterative Device 50
3.6.1 Observation 50
3.6.2 Motivation 51
3.6.3 Proposed Solution 51
3.7 Symbol Timing Problem 54
3.7.1 Observation 54
3.7.2 Motivation 56
3.7.3 Proposed solution 56
Chapter 4 58
4.1 Parameters and Multi-path Models 58
4.2 What is Different from 802.11a 59
4.3 BER Performances 60
4.3.1 AWGN Cases 60
4.3.2 Narrow-band Noise 73
4.3.3 Impulse-like Noise 76
Chapter 5 79
5.1 Conclusion 79
5.2 Future Works 79
Reference 80
參考文獻 [1] M. Morelli and U. Mengali, “A comparison of pilot-aided channel estimation methods for OFDM systems,” IEEE Transactions on Signal Processing, Vol. 49, No. 12, pp. 3065-3073, Dec. 2001.
[2] S. B. Bulumulla, S. A. Kassam, S. S. Venkatesh, “An adaptive diversity receiver for OFDM in fading channels,” IEEE International Conference on Communications, Vol. 3, pp.1325-1329, June 1998.
[3] S. Gifford, C. Bergstrom, and S. Chuprun, “Adaptive and linear prediction channel tracking algorithm for mobile OFDM-MIMO applications,” IEEE Military Communications Conference, Vol. 2, pp. 1298-1302, Oct. 2005.
[4] J. H. Park, M. Oh, Y. H. Cho and D. J. Park, “New channel estimation scheme exploiting reliable decision feedback symbols for OFDM systems,” IEEE Consumer Electronics, International Conference, Vol. 7, pp. 367-368, Jan. 2006
[5] Y. Li, “Simplified channel estimation for OFDM systems with multiple transmit antennas,” IEEE Transaction on Wireless Communications, Vol. 1, No. 1, pp. 67-75, Jan. 2002.
[6] Z. S. Lin, T. L. Hong, and D.C. Chang, “Design of an OFDM System With Long Frame by the Decision-Aided Channel Tracking Algorithm,” 6th IEEE International Conference on Electro/Information Technology (EIT 2006), East Lansing, MI USA, May 7-10, 2006.
[7] J. Beek, M. Sandell, and P. B‥orjesson, “ML Estimation of Time and Frequency Offset in OFDM Systems,” IEEE Transaction on Signal Processing, Vol. 45, No. 7, pp. 1800 - 1805, July 1997.
[8] M. Chiani, “Introducing Erasure in Decision-feedback Equalization to Reduce Error Propagation,” IEEE Transaction on Communications, Vol. 45, No. 7, pp. 757-760, July, 1997.
[9] Mathew, Y. X. Lee, Krachkovsky, and V. Yu., “A novel threshold technique for minimizing error propagation in MDFE read channel,” IEEE Global Telecommunications Conference, Vol. 6, pp. 3362 – 3367, Nov. 1998.
[10] M. Reuter, J. C. Allen, R. Zeidler, and C. North, “Mitigating Error Propagation Effects in a Decision Feedback Equalizer,” IEEE Transactions on Communications, Vol. 49, No. 11, pp. 2028-2041, November 2001.
[11] Roman, T. Enescu, and M. Koivunen, “Time-domain method for tracking dispersive channels in OFDM systems,” IEEE Vehicular Technology Conference,Vol. 2, pp. 1318–1321, April 2003.
[12] Werner, S. Enescu, and M. Koivunen, “Low-complexity time-domain channel estimators for mobile wireless OFDM systems,” IEEE Workshop on Signal Processing Systems Design and Implementation, Vol. 2, pp. 245-250, November 2005.
指導教授 張大中(Dah-Chung Chang) 審核日期 2007-7-10
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