Comparison of two methods for I/Q imbalance compensation applied in RF power amplifiers

S. A. Juárez-Cázares, E. Allende-Chávez, Y. Sandoval-Ibarra, J. R. Cárdenas-Valdez, E. Tlelo-Cuautle, J. C. Nuñez-Pérez

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Resumen

In this paper, the design and implementation of two methods for I/Q imbalance compensation is presented, based on a low cost phase measurement approach. The design methodology for an I/Q imbalance correction system is presented based on a DSP-FPGA board. The first method employs some trigonometric properties. The second employs Volterra series to model the non-linear behavior of the I/Q imbalance. The system performance is verified using a complex signal with phase and amplitude imbalance. The implemented systems have the advantage of having low implementation cost and a high design flexibility, which allows for future revisions or enhancement. The Stratix III FPGA board from Altera is employed for the practical implementation and results verification of the system. A comparison between methods is introduced for correcting (I or Q) branches respectively to guarantee amplitude and phase balancing condition in the modulator output. Experimental results are implemented employing an FPGA by using DSP-Builder to bit true VHDL hardware description of proposed model. This work can be considered as a low cost alternative for I/Q imbalance correction given that it does not require additional measurement equipment nor uses complex algorithms.

Idioma originalInglés
Título de la publicación alojadaNumerical and Evolutionary Optimization – NEO 2017
EditoresOliver Schutze, Leonardo Trujillo, Yazmin Maldonado, Paul Valle
EditorialSpringer Verlag
Páginas275-294
Número de páginas20
ISBN (versión impresa)9783319961033
DOI
EstadoPublicada - 2019
Evento5th Workshop on Numerical and Evolutionary Optimization, NEO 2017 - Tijuana, México
Duración: 27 sep. 201729 sep. 2017

Serie de la publicación

NombreStudies in Computational Intelligence
Volumen785
ISSN (versión impresa)1860-949X

Conferencia

Conferencia5th Workshop on Numerical and Evolutionary Optimization, NEO 2017
País/TerritorioMéxico
CiudadTijuana
Período27/09/1729/09/17

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