Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.584357
Title: Nonlinear data utilization : direct data look-up to behavioural modelling
Author: Qi, Hao
Awarding Body: Cardiff University
Current Institution: Cardiff University
Date of Award: 2008
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Abstract:
Newly developed communication systems put strict requirements on the performance of RF power amplifiers. A key issue for the development of RF PA is the inherent nonlinearity of power amplifiers hindering its integration with the well established small-signal development infrastructure which forms a closely interlinked chain of measurement systems, small-signal models and CAD based simulation and design software. The linkage between these components is provided by common small-signal data import and export file formats ensuring a bidirectional data exchange without any loss of the small-signal information. However, no equivalent infrastructure exists for a large-signal design process inhibiting the development of RF power amplifiers and other nonlinear components. This work demonstrates a coherent methodology aiming to provide equivalent infrastructure for large signal design process as already exists in small signal design process. As first part of the methodology, a new approach is proposed to directly import measured current and voltage waveforms, obtained from a typical Large Signal Network Analyser (LSNA) system recently developed in Cardiff University, into nonlinear CAD simulator for power amplifier design. This approach offers an efficient solution for using large signal characteristic data in CAD-based simulation and PA design as the simulation/design accuracy is guaranteed by measurement and the no lengthy data processing is required. The approach is implemented in Agilent ADS simulator and its validity is comprehensively verified on different devices and device technologies. Moreover, the potential of it in predicting device large signal performance when interpolation or extrapolation is needed is explored. As second part of the methodology, a new large signal nonlinear behavioural approach is proposed from behavioural modelling perspective as a complementation to the direct waveform utilization approach. The proposed modelling approach features in impressive simulation speed while maintaining excellent simulation accuracy. The modelling approach is developed on the basis of polynomial approximation and theoretical analysis shows that the approach can be considered as reasonable extension of S parameter design tool in large signal environment. It's demonstrated in this work that the model is extracted from large signal waveform data with specially designed parameter extraction procedure. The extracted model is verified on several devices and repeatable accuracy can be obtained even on high power devices such as 100w LDMOS. It's illustrated in this work that the above two distinctive approaches can be combined and nicely considered as parts of an integrated nonlinear measurement data utilization strategy. Such a strategy provides a fast and time efficient path to accurate CAD-based nonlinear design even at power levels relevant for base station applications.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.584357  DOI: Not available
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