Noise Impact on the Identification of DigitalPredistorter Parameters in the Indirect LearningArchitecture
2012 (English)In: 2012 Swedish Communication Technologies Workshop (Swe-CTW), IEEE conference proceedings, 2012, 36-39 p.Conference paper (Refereed)
The indirect learning architecture (ILA) is the mostused methodology for the identification of Digital Pre-distorter(DPD) functions for nonlinear systems, particularly for highpower amplifiers. The ILA principle works in black box modelingrelying on the inversion of input and output signals of thenonlinear system, such that the inverse is estimated. This paperpresents the impact of disturbances, such as noise in the DPDidentification. Experiments were performed with a state-of-artDoherty power amplifier intended for base station operationin current telecommunication wireless networks. As expected,a degradation in the performance of the DPD (measured innormalized mean square error (NMSE)) is found in our experiments.However, adjacent channel power ratio (ACPR) canbe a misleading figure of merit showing improvement in theperformance for wrongly estimated DPD functions.
Place, publisher, year, edition, pages
IEEE conference proceedings, 2012. 36-39 p.
Digital Predistortion, Noise Impact, Indirect learning architecture
Signal Processing Telecommunications
IdentifiersURN: urn:nbn:se:hig:diva-13508DOI: 10.1109/Swe-CTW.2012.6376285ScopusID: 2-s2.0-84871878986ISBN: 978-1-4673-4763-1OAI: oai:DiVA.org:hig-13508DiVA: diva2:575195
2012 Swedish Communication Technologies Workshop (Swe-CTW)