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A Parameter-Reduced Volterra Model for Dynamic RF Power Amplifier Modeling based on Orthonormal Basis Functions
Department of Electronics, University of Gävle.
Department of Electronics, University of Gävle.
2007 (English)In: International Journal of RF and Microwave Computer-Aided Engineering, ISSN 1096-4290, E-ISSN 1099-047X, Vol. 17, no 6, 542-551 p.Article in journal (Refereed) Published
Abstract [en]

A nonlinear dynamic behavioral model for radio frequency power amplifiers is presented. It uses orthonormal basis functions, Kautz functions, with complex poles that are different for each nonlinear order. It has the same general properties as Volterra models, but the number of parameters is significantly smaller. Using frequency weighting the out-of-band model error can be reduced. Using experimental data it was found that the optimal poles were the same for different input powers and for the different nonlinear orders. The optimal poles were also the same for direct and inverse models, which could be explained theoretically to be a general property of nonlinear systems with negligible linear memory effects. The model can be used as either a direct or inverse model with the same model error for power amplifiers with negligible linear memory effects.

Place, publisher, year, edition, pages
2007. Vol. 17, no 6, 542-551 p.
Keyword [en]
Inverse problems; Nonlinear distortion; Orthogonal functions; Parameter reduction; Power amplifiers; Radio transmitters
National Category
Telecommunications
Identifiers
URN: urn:nbn:se:kth:diva-7099DOI: 10.1002/mmce.20253ISI: 000250212400004OAI: oai:DiVA.org:kth-7099DiVA: diva2:12009
Note
QC 20100716. Uppdaterad från In press till Published 20100716.Available from: 2007-05-14 Created: 2007-05-14 Last updated: 2010-08-24Bibliographically approved
In thesis
1. Radio Frequency Power Amplifiers: Behavioral Modeling, Parameter Reduction, and Digital Predistortion
Open this publication in new window or tab >>Radio Frequency Power Amplifiers: Behavioral Modeling, Parameter Reduction, and Digital Predistortion
2007 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This work considers behavioral modeling, parameter-reduction, and digital predistortion of radio frequency power amplifiers. Due to the use of modern digital modulation methods, contemporary power amplifiers are frequently subjected to signals characterized by considerable bandwidths and fast changing envelopes. As a result, traditional quasi-memoryless amplitudeto-amplitude (AM/AM) and amplitude-to-phase (AM/PM) characteristics are no longer sufficient to describe and model the behavior of power amplifiers; neither can they be successfully used for linearization. In this thesis, sampled input and output data are used for identification and validation of several block structure models with memory. The time-discrete Volterra model, the Wiener model, the Hammerstein model, and the radial-basis function neural network are all identified and compared with respect to in-band and out-of-band errors. Two different signal types (multitones and noise), with different powers, peak-to-average ratios, and bandwidths have been used as inputs to the amplifier. Furthermore, two different power amplifiers were investigated, one designed for third generation mobile telecommunication systems and one for second generation systems.

A stepped three-tone measurement technique based on digitally modulated baseband signals is also presented. The third-order Volterra kernel parameters were determined from identified intermodulation products. The symmetry properties of the Volterra kernel along various portions of the three dimensional frequency space were analyzed and compared with the symmetry of the Wiener and Hammerstein systems.

Place, publisher, year, edition, pages
Stockholm: KTH, 2007. x, 59 p.
Series
Trita-EE, ISSN 1653-5146 ; 2007:010
National Category
Telecommunications
Identifiers
urn:nbn:se:kth:diva-24198 (URN)978-91-7178-589-3 (ISBN)
Public defence
2007-05-25, Sal 99:131, Högskolan i Gävle, Kungsbäcksvägen 47, Gävle, 13:00
Opponent
Supervisors
Note
QC 20100824Available from: 2010-08-24 Created: 2010-08-24 Last updated: 2011-09-08Bibliographically approved

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