Influence of Non Quadrature of Phase Shifter to Adaptive Interference Cancellation System

This paper investigates the influence of non quadrature of phase shifter to the convergence characteristic and interference cancellation ratio (ICR) of a Single chunnel analog adaptive interference cancellation system (SAAICS). We established the analysis model and solved the transient and steady-state characteristics of weights. Through the analysis of steady-state error and ICR, we obtained the rule of ICR variation with quadrature offset angle. And that rule with different interference signal phase was gained. The non quadrature of phase shifter decreases the average convergence speed. The more quadrature offset is, the low average convergence speed will be. But the ICR does not decrease absolutely with the increase of quadrature offset. It is related with the interference signal phase. For different interference signal phase, the rules of ICR variation with different quadrature offset angles are nearly consistent. The analyses are in agreement with the computer simulation. For non quadrature of phase shifter, the system is time-variant. When the signal frequency is higher, the influence of the time-variation is smaller.

[1]  B. Widrow On the statistical efficiency of LMS algorithms , 2004, Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004..

[2]  B. Widrow,et al.  Adaptive filtering in the frequency domain , 1978, Proceedings of the IEEE.

[3]  Chien-Cheng Tseng,et al.  Complex adaptive IIR notch filter algorithm and its applications , 1994 .

[4]  Yutaka Fukui,et al.  A new algorithm for adaptive notch filter with sub-band filtering , 2001, ISCAS 2001. The 2001 IEEE International Symposium on Circuits and Systems (Cat. No.01CH37196).

[5]  Dennis R. Morgan,et al.  An analysis of multiple correlation cancellation loops with a filter in the auxiliary path , 1980, ICASSP.

[6]  B. Widrow,et al.  Stationary and nonstationary learning characteristics of the LMS adaptive filter , 1976, Proceedings of the IEEE.

[7]  J. Glover Adaptive noise canceling applied to sinusoidal interferences , 1977 .

[8]  Bernard Widrow,et al.  On the statistical efficiency of the LMS algorithm with nonstationary inputs , 1984, IEEE Trans. Inf. Theory.

[9]  Bernard Widrow,et al.  On the statistical efficiency of the LMS family of adaptive algorithms , 2003, Proceedings of the International Joint Conference on Neural Networks, 2003..

[10]  B. Widrow,et al.  Adaptive noise cancelling: Principles and applications , 1975 .