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Power Amplifier Behavioral Modeling Performance Comparison of the LSNA and the Modulation-Domain System
KTH, School of Electrical Engineering (EES), Signal Processing.
2008 (English)In:  72ND ARFTG MICROWAVE MEASUREMENT SYMPOSIUM - TIME DOMAIN AND FREQUENCY DOMAIN MEASUREMENT     , New York: IEEE , 2008, 73-78 p.Conference paper, Published paper (Refereed)
Abstract [en]

The performance of power amplifier behavioral models depends strongly on the performance of the system used to measure the amplifiers. In this study two different systems with nonlinear measurement capability are used to model a commercially available PA. One system is a large-signal network analyzer (LSNA) and the second system is a modulation-domain system (MDS) consisting of a vector signal generator and a vector signal analyzer.

The PA was tested with multitone and WCDMA signals and behavioral models were extracted from the measured data. The evaluation criteria normalized mean square error and weighted error spectral power ratio or adjacent channel error power ratio were then computed to compare the performance of the models from the two systems. Cross-validation between the systems, using data from one system to obtain the model and validating its performance with data from the other system, shows that the model performance is mainly affected by the used validation data. Validating the performance of models from the LSNA with data from the MDS indicates that the identified models have almost the same performance as the MDS-identified models, i.e. it does not matter which system is used to identify the models. Cross-validation using a WCDMA-signal and multitone signal from the different systems shows that the normalized mean square error is mainly affected by modeling imperfections introduced by using another signal type. WESPR and ACEPR show a certain difference in performance with somewhat lower values for the MDS. The behavior of the two systems can be explained by different noise levels.

Place, publisher, year, edition, pages
New York: IEEE , 2008. 73-78 p.
Keyword [en]
Block codes, Electric network analysis, Heterojunction bipolar transistors, Mean square error, Power amplifiers, Signal generators
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-11675DOI: 10.1109/ARFTG.2008.4804282ISI: 000270442000013ISBN: 978-1-4244-2299-9 (print)OAI: oai:DiVA.org:kth-11675DiVA: diva2:279204
Conference
72nd ARFTG Microwave Measurement Conference, Portland, OR, DEC 09-12, 2008 ARFTG; MTT S; IEEE
Note
QC 20101015Available from: 2009-12-02 Created: 2009-12-02 Last updated: 2010-10-15Bibliographically approved
In thesis
1. On Radio Frequency Behavioral Modeling: Measurement Techniques, Devices and Validation Aspects
Open this publication in new window or tab >>On Radio Frequency Behavioral Modeling: Measurement Techniques, Devices and Validation Aspects
2009 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [sv]

Effektförstärkare för radiofrekvensapplikationer utgör fortfarande ett av de största problemen i trådlösa kommunikationssystem. Detta beror på att dessa förstärkare är ickelinjära, har låg energieffektivitet och ger mycket distortioner. Bättre verktyg för att förstå och korrigera dessa beteenden är nödvändiga. Ett sådant verktyg är beteendemodellering. En beteendemodell kan ses som en svart låda med insignal(er) och utsignal(er). In detta fall är dessa signaler samplade basbandssignaler och den svarta lådan är en matematisk relation mellan en insignal och en utsignal.

Avhandlingen behandlar några krav för beteendemodellering av nämnda system genom att presentera metoder för utvärdering och förbättring av modellernas prestanda. Detta åstadkoms genom att betrakta ett frekvensviktat felkriterium. Ett högpresterande mätsystem är också nödvändigt för experimenten. Prestandan hos det tillgängliga systemet jämförs med prestandan hos ett allmänt erkänt mätsystem, en s.k. storsignalsnätverksanalysator, genom att betrakta prestandan hos beteendemodellerna som extraheras och valideras med data från respektive mätsystem. Resultatet visar att det existerande mätsystemet har god prestanda.

Ett stort problem vid beteendemodellering är att kunna sampla med tillräckligt hög hastighet. Genom att använda Zhu-Franks generaliserade samplingsteorem vid beteendemodellering kan en del av detta problem undvikas. Teoremet medför att man kan sampla med en väsentligt lägre samlingsfrekvens än vad Nyquistteoremet säger. Modeller extraheras och prestandan utvärderas genom att använda kriteriet normalized mean square error (NMSE).

För stabil prediktion och korrektion av utsignalen måste robustheten hos de använda modellerna verifieras. En sådan studie som berör robustheten mot variationer i lastimpedansen har genomförts. Prestandan på direkta modeller försämras med 7 dB mätt som adjacent channel error power ratio (ACEPR). Prestanda på inversmodellen, implementerad som digital predistortion, försämras med upp till 13 dB mätt som adjacent channel power ratio (ACPR).

Abstract [en]

Radio frequency (RF) power amplifiers (PA) are still the most troublesomepart of a wireless system due to their inherent nonlinearity, low powerefficiency and high distortions. Better tools are needed to understand and correct the undesirable behavior. Some of these tools are behavioral models. A behavioral model is often thought of as a black box with some inputs andsome outputs. In the case here these inputs are sampled signals which meansthat the modeling amounts to finding a mathematical relationship betweenthe input signal(s) and the output signal(s).

This thesis considers some requirements for behavioral modeling of said systems by presenting methods for general performance evaluation and improvement by considering a frequency weighted error criterion.

A high performance measurement system is also needed. The performance of the available system is compared to the performance of a well recognized system, the largesignal network analyzer (LSNA). The results show that the existing measurementsystem can extract behavioral models with the same performance as the LSNA and can give lower performance validation errors.

Still the need for higher bandwidths drives the measurement systems to the limits, especially the digital parts. By utilizing the so called Zhu-Frank generalized sampling theorem, behavioral modeling of a PA is done by using data acquired at a sampling rate lower than the Nyquist rate. Models of a PA are extracted and the performance is evaluated using the normalized meansquare error (NMSE) criterion. For prediction and correction of the output signals the stability of the models regarding changes must be investigated. One such study considering controlled variations on the output load of the PA is done and both the predictive and corrective capabilities of the models are evaluated. The predictive capability gets up to 7 dB worse measured as adjacent channel error powerratio (ACEPR) and the corrective, as digital predistortion, gets up to 13 dB worse measured as adjacent channel power ratio (ACPR).

Place, publisher, year, edition, pages
Stockholm: KTH, 2009. vi, 65 p.
Series
Trita-EE, ISSN 1653-5146 ; 2009:056
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-11678 (URN)978-91-7415-526-6 (ISBN)
Presentation
2009-12-10, Hörsal 99131, Högskolan i Gävle, Kungsbäcksvägen 47, Gävle, 10:00 (English)
Opponent
Supervisors
Available from: 2009-12-09 Created: 2009-12-02 Last updated: 2010-10-15Bibliographically approved

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