Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/7736
標題: 應用於高階QAM調變系統之快速收斂盲蔽式等化器設計與實作
Design and Implementation of Fast Convergence Blind Equalizer for High-Order QAM Systems
作者: 梁文軒
Liang, Wen-Hsuan
關鍵字: Blind Equalizer;盲蔽式等化器;High-order QAM;MCMA;Multilevel Modulus;高階QAM;改良式固定模數演算法;多重準位模數
出版社: 電機工程學系所
引用: 1. 中文部分 [1] 鈦思科技股份有限公司,”視覺化建模環境 Simulink入門與進階” [2] 李偉,“可應用於高階QAM調變系統之混合成本函數盲蔽式等化器設計與FPGA實作”, 國立中興大學論文, 民國95年6月 [3] http://www.terasoft.com.tw [4] http://www.dgt.gov.tw 2. 西文部分 [5] John G. Proakis, Digital Communications, Fourth edition, McGraw-Hill, 2001. [6] Rodger E. Ziemer, William H. Tranter, Principles of Communications Systems, Modulation, and Noise, Fifth edition, Wiley, 2002. [7] D. Godard, ”Self-Recovering Equalization and Carrier Tracking in Two-Dimensional Data Communication Systems”, IEEE Transactions on Communications, vol. 28, pp. 1867-1875, 1980. [8] Nam Oh, K. and Ohk Chin, Y, “New Blind Equalization Techniques Based on Constant Modulus Algorithm”, IEEE Conference Global Telecommunications, vol. 2, pp 865-869, 1995. [9] Ching-Hsiang Tseng and Cheng-Bin Lin, “A Stop-and-Go Dual-Mode Algorithm for Blind Equalization”, IEEE Conference Global Telecommunications, vol. 2, pp.1427-1431, 1996. [10] Weerackody V. and Saleem A. Kassam, “Dual-Mode Type Algorithms for Blind equalization”, IEEE Transactions on Communications, volume 42, pp.22-28, 1994. [11] Michael J. Ready and Richard P. Gooch, “Blind Equalization Based On Radius Directed Adaption”, IEEE International Conference Speech, and Signal Processing, vol. 3, pp.1699-1701, 1990. [12] S. Chen, “Low Complexity Concurrent Constant Modulus Algorithm and Soft Decision Directed Scheme for Blind Equalization”, IEE Proceedings Image and Signal Processing, vol. 150, pp.312-320, 2003. [13] S. Chen, S. McLaughlin, P.M. Grant and B. Mulgrew, “Multi-Stage Blind Clustering Equaliser”, IEEE Transactions on Communications, vol. 43, pp.701-705, 1995. [14] J. Yang, J.-J. Werner, G. A. Dumont, “The Multimodulus Blind Equalization and Its Generalized Algorithms”, IEEE J. Sel. Areas Communication, vol. 20, no. 5, pp.997-1015, June 2002. [15] Kurakake T., Nakamura N., Oyamada K., “A Blind 1024-QAM Demodulator for Cable Television”, Int. Zurich Seminar on Communications (IZS), pp. 136-139, Feb. 2004. [16] S. Yoon, S. W. Choi, J. Lee, H. Kwon, and I. Song, “A Novel Blind Equalizer Based on Dual-Mode MCMA and DD Algorithm” 6th Pacific Rim Conference on Multimedia, Jeju Island, Korea, November 13-16, 2005, Part II, LNCS 3768, pp. 711-722, 2005. [17] K. N. OH, “A Single/Multilevel Modulus Algorithm for Blind Equalization of QAM Signals,” IEICE Trans. Vol. E80-A, No. 6, pp.1033-1038, June 1997. [18] H. N. King and Y. T. Lee and S.W. Kim, “Mathematical Modeling of VSB-Based Digital Television System”, ETRI Journal , vol. 25, no.1, pp.9-18, February 2003. [19] C. Dick, “Design and Implementation of High-Performance FPGA Signal Processing Datapaths for Software Defined Radios”, VMEbus Systems, Aug. 2001. [20] http://www.xilinx.com [21] http://www.mathworks.com [22] http://www.lyrtech.com
摘要: 
我們提出了一種有效率的盲蔽式等化器,盲蔽式等化器的演算法使用了兩階段單一/多重準位模數演算法並且可以應用於高階QAM(64/256/1024)調變系統中。我們所提出的盲蔽式等化器算法採用了兩階段收斂的方式是由改良式固定模數演算法(modified constant modulus algorithm,MCMA)以及決策運算(decision-directed,DD)推導而得,而且我們提出的盲蔽式等化器演算法成功地在64/256/1024QAM調變系統中使用數據機通道模型以及64QAM調變系統中使用ATTC通道模型的情況下完成模擬測試。等化器運作模式在第一階段時,結合改良式固定模數演算法以及決策運算來加快收斂,接著,當等化器的收斂情形達到一個可以接受的穩定狀態時,收斂偵測器(convergence detector)將等化器的運作模式切換到第二階段,切換至第二階段後,等化器的演算法改成採用多接模數的改良式固定模數演算法稱之為廣義型改良式固定模數演算法(generalized MCMA,GMCMA)以及決策運算,結合這兩種方式來更進一步降低均方誤差(mean square error,MSE)。
在64/256/1024調變系統中,我們提出的兩階段單一/多重準位模數演算法與其他相關的盲蔽式等化器演算法比較起來擁有最快速的收斂速度,在加入了收斂偵測器後雖然增加了額外的硬體成本,但是若能在適當的時機切換運作模式將可以使得等化器收斂的效能上有更好的表現,同時我們提出的演算法也可以提供不錯的MSE效能以及在相同訊號對雜訊比(signal to noise ratio,SNR)之下與其他方法相比可以得到最低的符元錯誤率(symbol error rate,SER)。最後我們在MATLAB與SimulinkTM的環境下進行盲蔽式等化器的實作,並且在SignalWAVeTM DSP+FPGA驗證平台上用FPGA做硬體的驗證。

An efficient blind equalization with the two-stage single/multilevel modulus and decision-directed (DD) algorithm is proposed for high-order QAM (64/256/1024QAM) systems. The proposed blind equalization algorithm applies the two-stage convergence scheme, which derives from the modified constant modulus algorithm (MCMA) and the DD algorithm. We successfully test the proposed blind equalization algorithm with the cable channel model for 64/256/1024QAM modulations and with the ATTC channel model for 64QAM modulation. In the first convergence stage, the mixed MCMA and DD equalization is applied for fast convergence. When the convergence process reaches to the acceptable steady state, the convergence detector will transform the equalization process into the second stage. In the second convergence stage, the MCMA with multiple modulus, called the generalized MCMA (GMCMA)method and DD algorithms are applied for further reducing the mean square error (MSE) of equalizations. In 64/256/1024QAM modulations, the proposed method performs faster convergence speed than the previous well-know blind equalization methods. By adding convergence detector, the equalizer will increase extra hardware costs. But when the switching mode is active at the right time, the equalizer will achieve better converged performance, compared with the other algorithms. Simultaneously, the proposed algorithm also provides better MSE performance and the minimum symbol error rate (SER) than the other methods at the same SNR. Finally, we implement the blind equalization on the MATLAB and SimulinkTM environment and do the FPGA emulation on the SignalWAVeTM DSP+FPGA board.
URI: http://hdl.handle.net/11455/7736
其他識別: U0005-2707200711584500
Appears in Collections:電機工程學系所

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