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研究生:陳蠡
研究生(外文):Chen Li
論文名稱:應用於高階正交振幅調變纜線通信之整合載波回復與快速多階模數盲蔽式等化器設計與FPGA實作
論文名稱(外文):Design and FPGA Implementation of Joint Carrier Recovery and Fast MLMA Blind Equalizer for High-order QAM Cable Communications
指導教授:范志鵬范志鵬引用關係
口試委員:黃穎聰王欣平
口試日期:2011-05-27
學位類別:碩士
校院名稱:國立中興大學
系所名稱:電機工程學系所
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2011
畢業學年度:99
語文別:中文
論文頁數:74
中文關鍵詞:盲蔽式等化器模數載波頻率偏移
外文關鍵詞:Blind EqualizerModulusCarrier Frequency Offset
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本篇論文中提出了一種使用具有快速收斂特性的多階模數演算法(Multi Level Modulus Algorithm,MLMA),並應用在擁有兩級反饋式等化器(FBE,Feed-Back Equalizer)與收斂偵測器的盲蔽式等化器上,此演算法可應用於64/256/1024正交振幅調變(Quadrature Amplitude Modulation,QAM),其中藉由模數的同心圓模切割可以有效的提高錯誤係數更新的準確率,並且由兩級反饋式等化器的架構來達到降低位元錯誤率(Bit Error Rate,BER)的功能,再由收斂偵測器來切換多階模數演算法的工作模式來增快等化器收斂的速度。

  收斂偵測器工作在獲取模式(Acquisition Mode)時,載波回復器(Carrier Recovery,CR)將會採用較大的更新係數來快速並且大幅度的追蹤載波頻率偏移(Carrier Frequency Offset,CFO),而當目前追蹤的頻率接近實際偏移頻率之後將會切換至追蹤模式(Tracking Mode),並改用較小的更新係數來緩慢並且小幅度的追蹤載波頻率偏移,如此一來就可以實現快速偵測載波頻率偏移並且幫助等化器快速收斂的目的。

  在等化器架構方面,為了降低位元錯誤率,故採用了兩級反饋式等化器的架構,藉由第一級反饋式等化器來提高星座點收斂的正確性,而第二級反饋式等化器則可以更進一步的提高星座點的收斂準確率,使得星座點收斂的位置更靠近原始的星座點,連帶使得位元錯誤率也隨之降低。

  我們不僅完成了軟體平台(Matlab)上浮點數與定點數的模擬,也更進一步的將模擬的結果實作為硬體。在硬體實作中選定了1024正交振幅調變等化器來作為實作的對象,並藉由FPGA的模擬平台(SMIMS)來驗證軟體模擬結果的正確性。


In this thesis, we propose an Multi-Level Modulus Algorithm(MLMA) that has fast convergence features and can be applied to the blind equalizer. We also use two-level feedback equalizers(FBE)and a convergence detector in the receiver design. This proposed MLMA algorithm can be used for 64/256/1024 Quadrature Amplitude Modulation(QAM)systems, and it seperated a single-region modulus to concentric circles of modulus, and then this work will raise updated precisions of error coefficients. The proposed two-level FBE architecture can reduce bit error rate (BER) further, and the convergence detector can switch working modes to increase the convergence speed of equalizations.

When the convergence detector works in the acquisition mode, the carrier recovery loop will choose bigger updated coefficients to track a large carrier frequency offset(CFO). When the acquisition frequency offset is close to the correct carrier frequency offset, the working mode of the convergence detector will be changed to the tracking mode, and updated coefficients will be replaced with smaller updated coefficients for tracking CFO accurately. By this scheme, we can achieve a fast CFO detection and a fast convergence of equalization.

In the equalizer architecture design, we use two-level FBE architecture to reduce the bit error rate. By the first level FBE, we can increase the correctness of constellation-point convergences. By the second level FBE, we can further increase precisions of constellation-point convergences. Thus, each received symbol can be close to the correct constellation positions, and the BER will be reduced.

We complete floating-point and fixed-point functional simulations in the MATLAB software platform, and we also implement the proposed design with hardware. In the hardware implementation, we realize a 1024 QAM equalizer, and verify the correctness of our design by the SMIMS FPGA-based hardware and software co-simulation platform.


目次

誌謝......................................................................................................................i
中文摘要... ...ii
英文摘要 iii
目次 iv
表目次 v
圖目次 vi

第一章 前言 1
1.1 動機 1
1.2 同軸電纜的特性與非理想效應 4
1.3 載波頻率偏移對傳輸訊號的影響 5
第二章 盲蔽式等化器架構與相關演算法 6
2.1 盲蔽式等化器的架構 6
2.2 固定模數演算法 10
2.3 改良式固定模數演算法 12
2.4 廣義多模數演算法 14
2.5 增強型硬性決策分類器 17
2.6 可變式步階調整器 18
2.7 載波頻率回復器 20
第三章 改良盲蔽式等化器與相關演算法的模擬與比較 23
3.1 改良盲蔽式等化器的架構 23
3.2 多階模數演算法 25
3.3 兩級式決策回授等化器 38
3.4 收斂偵測器 44
3.5 CMA、MLMA、MCMA、GMMA的模擬與比較 48
3.6 64QAM的模擬與比較 49
3.7 256QAM的模擬與比較 52
3.8 1024QAM的模擬與比較 55
第四章 高階QAM接收機的硬體實作 58
4.1 演算法的簡化與軟體定、浮點數的模擬 58
4.2 1024QAM等化氣的硬體架構設計 64
4.3 FPGA模擬平台簡述 68
4.4 使用Vericomm Pro介面驗證 69
第五章 結論與未來工作 71
參考文獻 72


參考文獻
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
[三] 白政達,“應用於高階QAM調變系統的盲蔽式等化與載波回復協同設計與模擬”, 國立中興大學論文, 民國97年7月
[四] 胡皓俊,“應用於高階QAM調變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”, 國立中興大學論文, 民國98年7月
[五] 徐婉寧,“應用於高階QAM調變系統之載波回復器與多模數盲蔽式等化器協同設計與分析”, 國立中興大學論文, 民國99年7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]J. Yang, J. J. Werner, and G. A. Dumont, "The Multimodulus Blind Equalization Algorithm," 13th Int. Conf. Digital Signal Processing, Santorini, Greece, July 1997.
[6]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.
[7]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.
[8] 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.
[9] 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.
[10] G.E. Hinton, S.J. Nowlan, “The Bootstrap Widrow-Hoff Rule as a Cluster-Formation Algorithm” Neural Computation, No.2, pp.355-362, 1990.
[11] 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.
[12] Z. Ding, "Adaptive Filters for Blind Equalization", in IEEE DSP Handbook, Douglas B. Williams, Ed., pp.24.1-24.17, IEEE Press, 1998.
[13] 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.
[14] 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
[15] Ching-Hsiang Tseng and Cheng-Bin Lin, “A Stop-and-Go Dual-ModeAlgorithm for Blind Equalization”, IEEE Conference GlobalTelecommunications, vol. 2, pp.1427-1431, 1996.
[16] 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.
[17] 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.
[18] 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.
[19] 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.
[20] M. Rupp and A.H. Sayed,“A time-domain feedback analysis of filtered-error adaptive gradient algorithms”, IEEE Trans. Signal Processing, vol. 44, pp.1428 – 1439, June 1996.
[21] B. Lin, R. He, X. Wang, and B. Wang,“Excess MSE analysis of the concurrent constant modulus algorithm and soft decision-directed scheme for blind equalisation”, IET Signal Processing, vol. 2, pp.147 – 155, June 2008.
[22] J. Mai and A.H. Sayed ,“A feedback approach to the steady-state performance of fractionally spaced blind adaptive equalizers”, IEEE Trans. Signal Processing, vol. 48, pp.80 – 91, Jan. 2000.


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