Comparison of direct learning and indirect learning predistortion architechtures

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

    Abstract

    Power amplifiers in a communication system are inherently nonlinear. Digital predistorters can compensate these nonlinearity effects. In this paper, two memory polynomial predistorters including direct and indirect learning architectures are compared with each other. To the best of our knowledge, no similar comparisons have been published. Both of these architectures are special cases of the self-tuning control. We have modeled predistorters and analysed nonlinear effects of a power amplifier and their digital compensation by using Matlab. Simulation results show that the memory polynomial model has convergence problems at large amplitudes and also problems of accuracy of representation. We observed that the results of the compensation depend also on the amplitude, not only on the frequency. The results of the linearisation show that the direct learning architecture achieves a better performance in almost all cases.
    Original languageEnglish
    Title of host publication2008 IEEE International Symposium on Wireless Communication Systems
    PublisherIEEE Institute of Electrical and Electronic Engineers
    Pages309-313
    ISBN (Electronic)978-1-4244-2489-4
    ISBN (Print)978-1-4244-2488-7
    Publication statusPublished - 30 Dec 2008
    MoE publication typeA4 Article in a conference publication

    Fingerprint

    Power amplifiers
    Data storage equipment
    Linearization
    Communication systems
    Tuning
    Polynomials
    Compensation and Redress
    Statistical Models

    Keywords

    • predistortion
    • power amplifier
    • constellation diagram
    • polynomials
    • nonlinear distortion
    • quadrature amplitude modulation

    Cite this

    Paaso, H., & Mämmelä, A. (2008). Comparison of direct learning and indirect learning predistortion architechtures. In 2008 IEEE International Symposium on Wireless Communication Systems (pp. 309-313). IEEE Institute of Electrical and Electronic Engineers .
    Paaso, Henna ; Mämmelä, Aarne. / Comparison of direct learning and indirect learning predistortion architechtures. 2008 IEEE International Symposium on Wireless Communication Systems. IEEE Institute of Electrical and Electronic Engineers , 2008. pp. 309-313
    @inproceedings{cdecbb6c9f994d779af88950230a7d76,
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    abstract = "Power amplifiers in a communication system are inherently nonlinear. Digital predistorters can compensate these nonlinearity effects. In this paper, two memory polynomial predistorters including direct and indirect learning architectures are compared with each other. To the best of our knowledge, no similar comparisons have been published. Both of these architectures are special cases of the self-tuning control. We have modeled predistorters and analysed nonlinear effects of a power amplifier and their digital compensation by using Matlab. Simulation results show that the memory polynomial model has convergence problems at large amplitudes and also problems of accuracy of representation. We observed that the results of the compensation depend also on the amplitude, not only on the frequency. The results of the linearisation show that the direct learning architecture achieves a better performance in almost all cases.",
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    Paaso, H & Mämmelä, A 2008, Comparison of direct learning and indirect learning predistortion architechtures. in 2008 IEEE International Symposium on Wireless Communication Systems. IEEE Institute of Electrical and Electronic Engineers , pp. 309-313.

    Comparison of direct learning and indirect learning predistortion architechtures. / Paaso, Henna; Mämmelä, Aarne.

    2008 IEEE International Symposium on Wireless Communication Systems. IEEE Institute of Electrical and Electronic Engineers , 2008. p. 309-313.

    Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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    AB - Power amplifiers in a communication system are inherently nonlinear. Digital predistorters can compensate these nonlinearity effects. In this paper, two memory polynomial predistorters including direct and indirect learning architectures are compared with each other. To the best of our knowledge, no similar comparisons have been published. Both of these architectures are special cases of the self-tuning control. We have modeled predistorters and analysed nonlinear effects of a power amplifier and their digital compensation by using Matlab. Simulation results show that the memory polynomial model has convergence problems at large amplitudes and also problems of accuracy of representation. We observed that the results of the compensation depend also on the amplitude, not only on the frequency. The results of the linearisation show that the direct learning architecture achieves a better performance in almost all cases.

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    Paaso H, Mämmelä A. Comparison of direct learning and indirect learning predistortion architechtures. In 2008 IEEE International Symposium on Wireless Communication Systems. IEEE Institute of Electrical and Electronic Engineers . 2008. p. 309-313