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New order selection technique using information criteria applied to SISO and MIMO systems predistortion

Published online by Cambridge University Press:  05 March 2013

M.V. Amiri ,
S.A. Bassam ,
M. Helaoui  and
F.M. Ghannouchi
M.V. Amiri*
Affiliation:
iRadio Laboratory Electrical and Computer Engineering Department, Schulich School of Engineering, University of Calgary, ICT Building, 2500 University Drive NW, Calgary, T2N 1N4, Canada. Phone: +1 (403) 210-5408
S.A. Bassam
Affiliation:
iRadio Laboratory Electrical and Computer Engineering Department, Schulich School of Engineering, University of Calgary, ICT Building, 2500 University Drive NW, Calgary, T2N 1N4, Canada. Phone: +1 (403) 210-5408
M. Helaoui
Affiliation:
iRadio Laboratory Electrical and Computer Engineering Department, Schulich School of Engineering, University of Calgary, ICT Building, 2500 University Drive NW, Calgary, T2N 1N4, Canada. Phone: +1 (403) 210-5408
F.M. Ghannouchi
Affiliation:
iRadio Laboratory Electrical and Computer Engineering Department, Schulich School of Engineering, University of Calgary, ICT Building, 2500 University Drive NW, Calgary, T2N 1N4, Canada. Phone: +1 (403) 210-5408
*
Corresponding author: M.V. Amiri Email: [email protected]
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Abstract

This paper presents a new order selection technique of matrix memory polynomial technique that models the nonlinearities of single-branch and multi-branch transmitters. The new criteria take into account the complexity of the model in addition to its mean-square error in the selection criteria. The quasi-convexity of the proposed criteria was proven in this work. By using this proposed Akaike information criterion (AIC) and Bayesian information criterion (BIC) criteria, the model order selection was cast as a cost minimization problem. To minimize the criteria, modified gradient descent and simulated annealing algorithms were utilized which resulted in a considerable reduction in the number of search iterations. The performances of the criteria were shown by comparing the normalized mean square error (NMSE) of a higher-order model and the optimum model. It has been shown that the NMSE difference is <0.5 dB, but the complexity is much smaller.

Keywords

AICBICMIMORF crosstalkRadio transmitterPolynomial modelGradient descentSimulated annealing
Type
Research Papers
Information
International Journal of Microwave and Wireless Technologies , Volume 5 , Special Issue 2: Special Issue on Power Amplifier Linearization , April 2013 , pp. 123 - 131
Copyright
Copyright © Cambridge University Press and the European Microwave Association 2013

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References

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