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研究生:黃俊穎
研究生(外文):Chun-Ying Huang
論文名稱:利用適應性反向QR分解遞迴式最小平方和演算法做正交調變器與解調器之增益及相位不平衡與直流偏差之補償
論文名稱(外文):Compensation For Gain/Phase Imbalance And DC Offset At Quadrature Modulator And Demodulator With Adaptive Inverse QRD-RLS Algorithm
指導教授:陳巽璋
指導教授(外文):Shiunn-Jang Chern
學位類別:碩士
校院名稱:國立中山大學
系所名稱:電機工程學系研究所
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:2002
畢業學年度:90
語文別:英文
論文頁數:54
中文關鍵詞:直流偏差正交調變增益與相位不平衡反相QR分解遞迴式最小平方和演算法預干擾器適應性濾波器補償
外文關鍵詞:Inverse QRD-RLS AlgorithmPredistorterQuadrature ModulationGain/Phase ImbalanceAdaptive FilterDC OffsetCompensation
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近來針對行動通訊的發射接收機的新設計有許多努力的成果,其中普遍的作法是結合射頻功能及數位訊號處理來得到線性的調變技術,並且使得調變器的樣式及接收機的處理能更具可塑性。但實際上,在正交調變器與解調器中,經常存在I-通道與Q-通道間的不平衡,這些不平衡主要是由於類比元件實現時,電容及電阻值的有限容忍度所導致,而這些I-通道與Q-通道間不可避免的不平衡降低了正交通訊技術的效能。
這篇論文中主要提出了一個新的盲目的架構,以及利用快速收斂的演算法,例如反相QR分解遞迴式最小平方和演算法(Inverse QRD-RLS),去解決以上所述在發射與接收機的補償問題。首先在發射機方面,我們將Inverse QRD-RLS演算法應用在一個利用功率量測作適應性估測及補償的方法,另外在接收機方面,利用量測機收信號的功率以及新的盲目適應性濾波器來達到非線性參數估測及補償的方法,被提出用來對正交解調器的增益及相位不平衡與直流偏差作適應性的補償。其中傳統的Inverse QRD-RLS演算法被使用來作參數估測及補償,並且不需要發射端傳送任何參考信號。在電腦模擬中,我們使用協調的16-PSK通訊系統來說明論文中所提出的架構之價值,而模擬結果證明我們所提出的方法相較於其他以存在的技術在消除不平衡與偏差之影響方面有相當大的改進,並且有較快的收斂速度以及在穩態時有較小的平均平方誤差。


There has been much effort in new design for transceiver used in mobile communications. The general approach is to combine RF functions with DSP to allow linear modulation techniques and permit flexibility of modulation format and receiver processing. In practice, with the quadrature modulation technique there is always some imbalance between the I- and Q channels of modulator and demodulator. This is mainly due to finite tolerances of capacitor and resistor values used to implement the analog components. The unavoidable imbalance between the I- and Q channels is known to degrade the performance of quadrature communication system.
The main concern of this thesis is to propose a new blind scheme and with fast convergence algorithm, such as the inverse QRD-RLS algorithm, to deal with the problem described above for compensation in the transmitter and receiver. First, for the transmitter, the so-called adaptive estimation and compensation with power measurement implemented by the inverse QRD-RLS algorithm is employed. While in the receiver, a new blind adaptive filtering approach of the nonlinear parameters estimation and compensation, along with the power measurement in the receiver, is devised to adaptively compensate for the gain/phase imbalance and DC offsets in a quadrature demodulator. Where the conventional inverse QRD-RLS algorithm is employed for estimating the parameters of compensator, without using any reference signal transmitted from the transmitter. To document the merits of the proposed scheme, computer simulation for the coherent 16-PSK-communication system is carried out. With our proposed method a great improvement for eliminating the effects of the imbalance and offset over the existing techniques has verified. It has rapidly convergence rate and the smaller mean square error in steady state.


Acknowledgementi
Abstractii
Contentsiii
List of Figuresv
Chapter 1 Introduction1
Chapter 2 Conventional Adaptive Compensation Techniques With Direct Conversion Structure
2.1 Introduction4
2.2 System Model Description5
2.3 Adaptive Compensation With Envelope Detection For Transmitter
12
2.3.1 Adaptive Compensation Of DC Offset14
2.3.2 Adaptive Compensation For Gain And Phase Imbalance15
2.4 Decision Directed Compensation For Receiver18
2.5 Linear Parameters Estimation And Compensation For Receiver19
2.6 Nonlinear Parameters Estimation And Compensation For Receiver
22
Chapter 3 New Adaptive Compensation Algorithm And Scheme With Direct Conversion Structure
3.1 Introduction25
3.2 A Volterra Predistorter Based On The Indirect Learning Architecture
26
3.3 Adaptive Estimation And Compensation With Power Measurement
31
3.4 Blind Adaptive compensation With Power Measurement35
3.4.1 Parameter Estimation And Compensation36
3.4.2 Recursive Implementation40
3.5 Computer Simulation Results41
Chapter 4 Conclusions51
References


[1] A. A. Abidi, “Direct-Conversion Radio Transceivers for Digital Communications,” IEEE Journal, Solid-State Circuits, vol. 30, pp. 1399-1410, Dec. 1995.[2] B. Razavi, “ Design Considerations for Direct- Conversion Receivers,” IEEE Trans. Circuits and Systems II, vol. 44, pp. 428-435, June 1997.[3] D. S. Hilborn, S. P. Stapleton, and J. K. Cavers, “An Adaptive Direct Conversion Transmitter,” IEEE Trans. Vehicular Technology, vol.43, pp. 223-233, Nov. 1994.[4] J. K. Cavers and M. W. Liao, “Adaptive Compensation for Imbalance and Offset Losses in Direct Conversion Transceivers,” IEEE Trans. Vehicular Technology, vol.42, pp. 581-588, Nov. 1993.[5] H. Nguyen, “Improving QPSK Demodulator Performance for Quadrature Receiver with Information from Amplitude and Phase Imbalance Correction,” WCNC, Sept. 2000.[6] X. Huang and M. Caron, “Adaptive Gain / Phase / DC Offset Compensation in Quadrature Modulators,” ISPACS ’01, Nashville, Tennessee, USA, Nov. 2001.[7] J. P. F. Glas, “Digital I / Q Imbalance Compensation in A Low-IF Receiver,” Proc. IEEE Globecom, pp. 1461-1466, Nov. 1998.[8] M. Valkama and M. Renfors, “Advanced DSP for I / Q Imbalance Compensation in A Low-IF Receiver,” Proc. IEEE int. Conf. Commun., pp. 768-772, June 2000.[9] M. Valkama, M. Renfors and V. Koivunen, “Blind Source Separation Based I/Q Imbalance Compensation,” Proc. IEEE Symp. Adaptive Syst. Signal Process., Commun., Contr., pp.310-314, Oct. 2000.[10] L. Yu and W. M. Snelgrove, “A Novel Adaptive Mismatch Cancellation System for Quadrature IF Radio Receivers,” IEEE Trans. Circuits Syst. II, vol. 46, pp. 789-801, June 1999.[11] M. Valkama, M. Renfors and V. Koivunen, “Advanced Methods for I/Q Imbalance Compensation in Communication Receivers,” IEEE Trans. Signal Processing, vol. 49, pp.2335-2344, Oct. 2001.[12] S. J. Chern and C. H. Huang, “Nonlinear Adaptive Equalizer Based Upon an Inverse QRD-RLS Volterra Filter,” Proc. Of 1997 IEEE MICC/ISPACS’97, Nov. 11-13, Hotel Nikko, Kuala Lumpur, Malaysia, pp.S24.1.1-S24.1.5, Nov. 1997.[13] C. Eun and E.J. Powers, “A New Volterra Predistorter Based on the Indirect Learning Architecture,” IEEE Trans. Signal Processing, vol. 45, pp.223-227, Jan. 1997.[14] S. T. Alexander, A. L. Ghirnikar, “A Method for Recursive Least Squares Filtering Based Upon an Inverse QR Decomposition,” IEEE Trans. Signal Processing, vol. 41, pp.20-30, Jan. 1993.[15] G. Lazzarin, S. Pupolin, and A. Sarti, “Nonlinearity Compensation in Digital Radio Systems,” IEEE Trans. on Commun., vol. 42, pp.988-999, Feb. 1994.[16] D. Psaltis, A. Siders, and A. A. Yammamura, “A Multilayer Neural Network Controller,” IEEE Contr. Syst. Mag., pp.17-21, Apr. 1988.[17] M. Faulkner, T. Mattson, and W. Yates, “Automatic Adjustment of Quadrature Modulators,” Electron. Lett., vol. 27, no. 3, pp.214-216, 1991.[18] S. Haykin, Adaptive Filter Theory, 3rd ed., Prentice-Hall, Upper Saddle River, New Jersey, 1996.[19] J. G. Proakis, Digital Communications, 4rd ed., McGraw-Hill, 2001.[20] M. Schetzen, The Volterra and Wiener Theories of the Nonlinear System, New York, Wiley, 1980.

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