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A Study of memory effects of RF power LDMOS before and after digital predistortion
University of Gävle, Department of Technology and Built Environment, Ämnesavdelningen för elektronik. University of Gävle, Center for RF Measurement Technologies.
University of Gävle, Department of Technology and Built Environment, Ämnesavdelningen för elektronik. University of Gävle, Center for RF Measurement Technologies.
University of Gävle, Center for RF Measurement Technologies. (Ericsson AB)
(Infineon Technologies North America Corp.)
2009 (English)In: Wireless and Microwave Technology Conference, 2009. WAMICON '09. IEEE 10th Annual, 2009, 1-5 p.Conference paper, Published paper (Refereed)
Abstract [en]

Sideband asymmetries in distortion products are created due to electrical and thermal memory effects and this can be difficult to correct for in a digital predistortion algorithm. In this study, sideband asymmetries in third-order intermodulation distortion products before and after digital predistortion were investigated using 2-tone and 2-carrier WCDMA signals. The parallel Hammerstein (PH) model was used in the digital predistortion algorithm. The sign of the asymmetries before correction were found to depend on power level. Memoryless correction lead to an increase in asymmetries for some power ranges whereas using a PH model of order 13 with only one order of memory length lead to good correction over a large power range.

Place, publisher, year, edition, pages
2009. 1-5 p.
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:hig:diva-5559DOI: 10.1109/WAMICON.2009.5207289ISI: 000272995600024ISBN: 978-1-4244-4564-6 (print)OAI: oai:DiVA.org:hig-5559DiVA: diva2:241788
Conference
2009 IEEE 10th Annual Wireless and Microvave Technology Conference
Available from: 2009-10-05 Created: 2009-10-05 Last updated: 2012-01-15Bibliographically 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 kanses som en svart låda med insignal(er) och utsignal(er). In detta fall är dessasignaler 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 validerasmed 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 prestandanutvärderas 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 troublesome part 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 and some outputs. In the case here these inputs are sampled signals which means that the modeling amounts to finding a mathematical relationship between the 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 large signal network analyzer (LSNA). The results show that the existing measurement system 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 mean square 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 power ratio (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: Skolan för elektro- och systemteknik, Kungliga Tekniska högskolan, 2009. 65 p.
Series
TRITA-EE 2009:056, ISSN 1653-5146
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:hig:diva-6699 (URN)978-91-7415-526-6 (ISBN)
Presentation
2009-12-10, Hörsal 99131, Kungsbäcksvägen 47, Gävle, 08:47 (English)
Opponent
Supervisors
Available from: 2010-04-28 Created: 2010-04-22 Last updated: 2010-04-28Bibliographically approved

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