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標題: 應用於高階QAM通信系統之混合廣義多模數與軟性決策快速盲蔽式等化器設計與模擬
Design and Simulation of Joint GMMA and SDD Fast Blind Equalizer for High-order QAM System
作者: 胡皓峻
Hu, Hao-Jun
關鍵字: 多模數演算法;MMA;等化器;Blind Equalizer
出版社: 電機工程學系所
引用: 中文參考資料 [一] 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 [二] 梁文軒,“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”, 國立中興大學論文, 民國96年6月 英文參考資料 [1]D.Godard, ”Self-Recovering Equalization and Carrier Tracking in Two-Dimensional Data Communication Systems”, IEEE Transactions on Communications, vol. 28, pp. 1867-1875, 1980. [2]John G. Proakis, Digital Communications, Fourth edition, McGraw-Hill, 2001. [3]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. [4]A.R. Esam, “Blind Adaptive Equalization with Variable Step Size”, 4Th International Conference on Information & Communications Technology, Page(s):1 – 1, Dec. 2006. [5]Cheng-Yi Huang, Chih-Peng Fan, etc., “The Design and Simulation Tools for Cable Modem Physical Layer”, Technical Report, CCL/ITRI, Taiwan, 2001. [6]J. Yang, J. J. Werner, and G. A. Dumont, "The Multimodulus Blind Equalization Algorithm," 13th Int. Conf. Digital Signal Processing, Santorini, Greece, July 1997. [7]J. Karaoguz and S. H. A, “A Soft Decision Directed Blind Equalization Algorithm Applied to Equalization of Mobile Communication Channels,” in Proc. ICC, Vol.3, pp. 343.4.1-343.4.5 ,Chicago, USA, 1992. [8]S. Chen, E.S. Chng, “Concurrent Constant Modulus Algorithm and Soft Decision Directed Scheme for Fractionally-Spaced Blind Equalization,” in: Proceedings of the ICC, vol. 4, pp. 2342-2346, Paris, France, 2004. [9]Chih-Peng Fan, Wen-Hsuan Liang, Wei Lee, “Fast Blind Equalization with Two-Stage Single/Multilevel Modulus and DD Algorithm for High Order QAM Cable Systems,” IEEE International Symposium on Circuits and Systems, Seattle, USA, May 2008. [10]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. [11]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, Part II, pp. 711-722, Jeju Island, Korea, November 2005. [12]G.E. Hinton, S.J. Nowlan, “The Bootstrap Widrow-Hoff Rule as a Cluster-Formation Algorithm” Neural Computation, No.2, pp.355-362, 1990. [13]R. Johnson Jr., P. Schniter, T.J. Endres, J.D. Behm, D.R. Brown, R.A. Casas, "Blind equalization using the constant modulus criterion: a review," Proc. IEEE 86, pp. 1927-1950, Oct 1998. [14]Z. Ding, "Adaptive Filters for Blind Equalization", in IEEE DSP Handbook, Douglas B. Williams, Ed., pp.24.1-24.17, IEEE Press, 1998. [15]F.C.C. De Castro, M.C.F. De Castro, D.S. Arantes, “ Concurrent Blind Deconvolution for Channel Equalization”, Proc ICC’, vol.2, pp. 366-371, Finland, 2001. [16]Lin He, M.G. Amin, C. Reed, Jr., R.C. Malkemes, “A Hybrid Adaptive Blind Equalization Algorithm for QAM Signals in Wireless Communications”, IEEE Transactions on Signal Processing, Vol.52, pp. 2058 – 2069, July 2004 [17]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. [18]K. Banović, E. Abdel-Raheem, M.A.S. Khalid, “A Novel Radius-Adjusted Approach for Blind Adaptive Equalization”, IEEE Signal Processing Letters, Vol.13, pp. 37 - 40, Jan. 2006. [19]K. Banović, M.A.S. Khalid, E. Abdel-Raheem, “A configurable fractionally-spaced blind adaptive equalizer for QAM demodulators”, IEEE International Symposium on Signal Processing and Information Technology, pp. 150 – 153, Dec. 2007. [20]A. Beasley, A. Cole-Rhodes, “A Blind Decision Feedback Equalizer for QAM Signals based on the Constant Modulus Algorithm”, IEEE International Symposium on Military Communications Conference, pp. 1 – 7, 2006. [21]S. Barbarossa and A. Scaglione, "Blind Equalization Using Cost Functions Matched to the Signal Constellation", in Proc. 31st Asilomar Conf. Sig. Sys. Comp., Pacific Grove, CA, November 1997. [22]Wei Rao, Yingge Han, Yecai Guo, “A New Family of Combination Blind Equalization with A New Constant Modulus Algorithm Based on Variable Slope Error Function”, The 8th International Conference on Signal Processing, Vol.3, 2006
本篇論文針對了64/256/1024QAM等高階QAM的傳輸系統提出了一種快速收斂的兩級式混合廣義多模數演算法(Generalized Multi-Modulus Algorithm,GMMA)及軟性決策運算(Soft Decision-Directed,SDD)的盲蔽等化器。藉由兩級式的方法,將等化器的收斂時間加快,並進一步的降低穩態的均方誤差(Mean Square Error,MSE)。
接著再將我們的演算法與其它不同的演算法一起比較,得到在相同通道環境下我們所提出的演算法具有較快的收斂速度及較低的均方誤差,而且在相同的雜訊比(Signal-to-Noise Ratio,SNR)下有最低的符元錯誤率(Symbol Error Rate,SER)。之後再搭配回授決策等化器(Decision Feedback Equalizer,DFE),可以再加強等化器的效果。最後,我們將兩級式混合廣義多模數演算法演算法做硬體上的化簡,並將此演算法做浮點數與定點數的模擬,比較兩者的均方誤差與符元錯誤率,找出硬體所需的精確度。

In this thesis, we propose a two-stage joint Generalized Multi-Modulus Algorithm (GMMA) and Soft Decision-Directed (SDD) blind equalizer for high-order QAM (64/256/1024QAM) systems. By applying the two-stage algorithm, it will speed up the time and will also reduce the stable Mean Square Error (MSE) for convergence.
In the first stage, the joint GMMA and SDD scheme is applied for the purpose of fast convergence. When the equalization approaches the threshold of convergence, the convergence detector switches the first stage equalization to the second stage equalization, where the SDD scheme is applied merely for the purpose of reducing the stable MSE in the second stage. In order to enhance the equalization, the GMMA part and the SDD part of the proposed algorithm utilizes the variable step-size manner and uses the modification SDD with adaptively selected decision region, respectively. The wired cable channel is applied for the simulation, and the derivation of the error function for the proposed algorithm is also accomplished.
It is noted that our proposed scheme performs faster convergence speed with the same channel environment and also achieves smaller MSE at the same SNR than the previous blind algorithms do. Then we also try to add the Decision Feedback Equalizer (DFE) in our method to reinforce the equalization performance again. Finally, we simplify the complexity of the proposed algorithm and compare the MSE and the Symbol error rate (SER) between the floating-point version and the fixed-point one in order to find the required precision of the hardware implementation.
其他識別: U0005-3007200911453200
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