Performance assessment of RF power amplifier memory polynomial models under different signal statistics

Jebali, Chokri; Gharsallah, Ali; Boulejfen, Noureddine; Ghannouchi, Fadhel M.

doi:10.1109/icecs.2009.5410910

Cited by 2 publications

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“…Memory polynomial model (MPM) has been widely used in the last decade for PA modeling due to the easiness in parameters extraction [43][44][45][46][47]. The system representation is illustrated in Fig.…”

Section: Memory Polynomial Modelmentioning

confidence: 99%

Digital Predistorion of 5G Millimeter-Wave Active Phased Arrays using Artificial Neural Networks

Jalili¹

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Section: Memory Polynomial Modelmentioning

confidence: 99%

Digital Predistorion of 5G Millimeter-Wave Active Phased Arrays using Artificial Neural Networks

Jalili¹

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Nonlinear power amplifier sensitivity and effects on behavioural model performance

Jebali

Boulejfen

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et al. 2011

Eighth International Multi-Conference on Systems, Signals &Amp; Devices

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basis in term of numerical stability and best fitting behaviour under different signal bandwidths and power Behavioural modelling of power amplifiers is significant for distributions.performance estimation efficiency. The numerical error is efficient to characterize a power amplifier models and signal 2. CHARACTERIZATION AND effects. Based on this characteristics, a different MODELING OF POWER AMPLIFIERS performance driven iterative methods for model parameters estimation are presented. We introduce methods for the matrix inversion problems of the model coefficients It has been taken that any nonlinearity in the transfer estimation. Indeed, due to numerical instability of system characteristic of a power amplifier constitutes a problem resolution in matrix inversion, two alternatives techniques of some kind, but no attempts have been made to are proposed to avoid the direct construction of the extreme quantify the problem.ill-conditioning. Accurate characterization based on both The iterative methods characteristic, is first proceeding orthogonal and conventional polynomial basis are applied to by successive approximations and the iteration counts is model PAs. Simulation results with real multi-carrier unknown to reach a given precision. Second the WCDMA signals are applied for coefficients extraction significant characteristic is the convergence of the with improved numerical stability. The effects of the signal iterative method, with self-correcting, i.e. if a characteristics on the performance of the device under test msaclto uigtepoesi ietebhvo (DUT aredemostraed.started again a new calculation from a new initial Index Terms-effeciency, power amplifier, vector. We note that, if a mistakes has been made, this polynomial model, memory effects, wideband signal. can possibly improve the convergence of the method by choosing a vector near the solution. Indeed, the consequences is a fast convergence, this characteristic is 1. INRODUTIONexploited more in practice [2].

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Performance assessment of RF power amplifier memory polynomial models under different signal statistics

Cited by 2 publications

References 2 publications

Digital Predistorion of 5G Millimeter-Wave Active Phased Arrays using Artificial Neural Networks

Digital Predistorion of 5G Millimeter-Wave Active Phased Arrays using Artificial Neural Networks

Nonlinear power amplifier sensitivity and effects on behavioural model performance

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