Estimation of the efficiency of compensation of nonlinear distortion of OFDM signals in nonlinear devices with a memory

V.Yu. Tikhonov – Post-graduate Student; Moscow Technical University of Communication and Informatic E-mail: sl-tx@yandex.ru

Estimation of the efficiency of compensation of nonlinear distortion of OFDM signals in nonlinear devices with a memory

V.Yu. Tikhonov – Post-graduate Student¹, Moscow Technical University of Communication and Informatic E-mail: sl-tx@yandex.ru²

research article UDC 621.391:519.27 Pages: 54-59

¹ аспирант, Московский технический университет связи и информатики
² д.т.н., профессор, зав. кафедрой радиотехнических систем, Московский технический университет связи и информатики

Keywords: nonlinear distortion predistortion power amplifier OFDM signal

Abstract

For OFDM signals by means of simulation the estimates of improving the quality of transmission of the digital communication system with the introduction of compensation algorithms for nonlinear inertial devices are obtained. It is shown that the use of such algorithms significantly reduces the probability of error in the transmission of information bits.

How to cite

Тихонов В.Ю., Шинаков Ю.С. Оценка эффективности компенсации нелинейных искажений сигналов OFDM в нелинейных инерционных устройствах // Радиотехника. 2018. № 3. С. 54–59.

References

Kerry Schutz, Dick Benson. Adaptive DPD design. MathWorks. https://www.mathworks.com/matlabcentral/fileexchange/45890adaptive-dpd-design.
Lim Y.H., Cho Y.S., Cha I.W., Youn D.H. An adaptive nonlinear prefilter for compensation of distortion in nonlinear systems. IEEE Tran. on Signal Processing. 1998. V. 46. № 6. P. 1726−1730.
Gao X.Y., Snelgrove W.M. Adaptive linearization of a loudspeaker. Proc. of IEEE International Conference on Acoustics, Speech and Signal Processing. Toronto (Canada). 1990. V. 5. P. 3589−3592.
Abd-Elrady E. A nonlinear approach to harmonic signal modeling // Signal Processing. 2002. V. 84. P. 163−195.
Abd-Elrady E. Nonlinear approaches to periodic signal modeling // Ph.d. thesis, Department of Information Technology, Uppsala University. Uppsala. Sweden. 2005.
Paaso H., Mämmela A. Comparison of Direct Learning and Indirect Learning Predistortion Architectures // Wireless Communication Systems. 2008. P. 309−313.
Gan L. Adaptive digital predistortion of nonlinear systems. Faculty of Electrical and Information Engineering. Ph.D thesis. Graz (Austria): Graz University of Technology. 2009. 120 p.
Gan L. Linearization of weakly nonlinear systems using FIR filters and Recursive Prediction Error method. https://www.researchgate.net/publication/224352766_Linearization_of_weakly_nonlinear_Volterra_systems_using_FIR_filters_and_rec ursive_prediction_error_method.
Gan L. Digital predistortion of memory polynomial systems using direct and indirect learning architectures https://www.researchgate.net/publication/255651307_Digital_Predistortion_of_memory_polynomial_systems_using_direct_and_indirec t_learning_architectures.
Ding L., Zhou G.T., Morgan D.R. et al. Memory polynomial predistorter based on the indirect learning architecture // Proc. of GLOBECOM. Taipei (Taiwan). 2002. V. 1. P. 967−971.
Schetzen M. The Volterra and Wiener Theories of Nonlinear Systems. Revised edition. Krieger Publishing Company. 2006. 618 p.
Kang H.W., Cho Y.S., Youn D.H. Adaptive precompensation of Wiener systems // IEEE Trans. on Signal Processing. 1998. V. 46. № 10. P. 2825−2829.
Ding L., Zhou G.T., Morgan D.R. et al. A robust digital baseband predistorter constructed using memory polynomials // IEEE Transactions on Communications. 2004. V. 52. P. 159−165.
Morgan D.R., Z. Ma, Kim J. et al. A generalized memory polynomial model for digital predistortion of RF power amplifiers // IEEE Trans. on Signal processing. 2006. V. 54. № 10. P. 3852−3860.
Soderstrom T., Stoica P. System Identification. Hemel Hempstead United Kingdom: Prentice-Hall International. 1989. 612 p.
Levin B.R. Teoreticheskie osnovy’ statisticheskoj radiotexniki. M.: Sov. radio. 1974.

[1] Kerry Schutz, Dick Benson. Adaptive DPD design. MathWorks. https://www.mathworks.com/matlabcentral/fileexchange/45890adaptive-dpd-design.

[2] Lim Y.H., Cho Y.S., Cha I.W., Youn D.H. An adaptive nonlinear prefilter for compensation of distortion in nonlinear systems. IEEE Tran. on Signal Processing. 1998. V. 46. № 6. P. 1726−1730.

[3] Gao X.Y., Snelgrove W.M. Adaptive linearization of a loudspeaker. Proc. of IEEE International Conference on Acoustics, Speech and Signal Processing. Toronto (Canada). 1990. V. 5. P. 3589−3592.

[4] Abd-Elrady E. A nonlinear approach to harmonic signal modeling // Signal Processing. 2002. V. 84. P. 163−195.

[5] Abd-Elrady E. Nonlinear approaches to periodic signal modeling // Ph.d. thesis, Department of Information Technology, Uppsala University. Uppsala. Sweden. 2005.

[6] Paaso H., Mämmela A. Comparison of Direct Learning and Indirect Learning Predistortion Architectures // Wireless Communication Systems. 2008. P. 309−313.

[7] Gan L. Adaptive digital predistortion of nonlinear systems. Faculty of Electrical and Information Engineering. Ph.D thesis. Graz (Austria): Graz University of Technology. 2009. 120 p.

[8] Gan L. Linearization of weakly nonlinear systems using FIR filters and Recursive Prediction Error method. https://www.researchgate.net/publication/224352766_Linearization_of_weakly_nonlinear_Volterra_systems_using_FIR_filters_and_rec ursive_prediction_error_method.

[9] Gan L. Digital predistortion of memory polynomial systems using direct and indirect learning architectures https://www.researchgate.net/publication/255651307_Digital_Predistortion_of_memory_polynomial_systems_using_direct_and_indirec t_learning_architectures.

[10] Ding L., Zhou G.T., Morgan D.R. et al. Memory polynomial predistorter based on the indirect learning architecture // Proc. of GLOBECOM. Taipei (Taiwan). 2002. V. 1. P. 967−971.

[11] Schetzen M. The Volterra and Wiener Theories of Nonlinear Systems. Revised edition. Krieger Publishing Company. 2006. 618 p.

[12] Kang H.W., Cho Y.S., Youn D.H. Adaptive precompensation of Wiener systems // IEEE Trans. on Signal Processing. 1998. V. 46. № 10. P. 2825−2829.

[13] Ding L., Zhou G.T., Morgan D.R. et al. A robust digital baseband predistorter constructed using memory polynomials // IEEE Transactions on Communications. 2004. V. 52. P. 159−165.

[14] Morgan D.R., Z. Ma, Kim J. et al. A generalized memory polynomial model for digital predistortion of RF power amplifiers // IEEE Trans. on Signal processing. 2006. V. 54. № 10. P. 3852−3860.

[15] Soderstrom T., Stoica P. System Identification. Hemel Hempstead United Kingdom: Prentice-Hall International. 1989. 612 p.

[16] Levin B.R. Teoreticheskie osnovy’ statisticheskoj radiotexniki. M.: Sov. radio. 1974.

Abstract

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