Implementation and Performance of DSP-Oriented Feedforward Power Amplifier Linearizer

A. Ghadam, Sascha Burglechner, A.H. Gokceoglu, Mikko Valkama, Andreas Springer

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, a digital signal processing-oriented implementation of feedforward power amplifier linearizer (DSP-FF) is introduced. In DSP-FF, the signal and error cancellation circuits are implemented, partially, in the DSP regime. By doing so, the number of bulky radio frequency (RF) components is reduced and their functionality is replaced by more flexible DSP circuitry and also various implementation nonidealities can be efficiently controlled. A two-stage estimation approach stemming from least-squares model fitting is proposed to identify proper DSP-FF coefficients. This improves the linearization performance by decoupling the effects of estimation inaccuracies between the two DSP-FF circuits. Furthermore, a comprehensive performance analysis of DSP-FF is carried out, taking also the memory of the core power amplifier into account. In particular, a closed-form expression for the intermodulation distortion reduction is derived in terms of the errors in the circuit coefficients. Also the measurement noise effects and large sample properties of the estimators are analyzed. The outcomes of computer simulated experiments verify the analytical results which are presented in this paper. Moreover, laboratory measurement setup utilizing a highly nonlinear RF power amplifier and contemporary telecommunication waveform demonstrates the linearization capability of the DSP-FF in terms of improvement in the measured adjacent channel leakage ratio.
Original languageEnglish
Article number6029951
Pages (from-to)409 - 425
Number of pages17
JournalIEEE Transactions on Circuits and Systems I: Regular papers
Volume59
Issue number2
DOIs
Publication statusPublished - Feb 2012

Fields of science

  • 202030 Communication engineering
  • 202037 Signal processing

JKU Focus areas

  • Mechatronics and Information Processing

Cite this