Low-IF and Zero-IF (direct conversion) down converters showed a great potential in implementing multi standard single chip solutions, eliminating the need to use off chip components and so reduce the area and the cost of the wireless receivers. One of the main performance limitations in the low-IF & Zero-IF down-converters is the components mismatch between the in-phase path and the quadrature-path named the IQ Imbalance (IQI) which limits the achievable image rejection ratio (IRR) of the down converters. Many techniques had been proposed to enhance the achievable IRR either by using calibration methods, e.g. using lab calibration, or by doing online compensation during signal reception. In this work those techniques are reviewed, proposing three new methods for blind IQI compensation techniques, the first proposed method targets the low input signal to interference ratio (low SIRin) while the second and third methods targets the moderate and high SIRin, showing that the proposed methods reach better performance and/or lower complexity than the methods already introduced in the literature. Also two techniques to perform data aided IQI compensation are introduced exploiting pilot symbols within the desired signal with no prior knowledge about the image signal. The first method exploits a preamble sequence assuming slow fading condition while the second approach exploits a sequence of pilots to compensate for the IQI being suitable for fast fading conditions as well. Simulation results showed that the proposed data aided techniques achieved shorter convergence time and higher image rejection ratio compared to the blind methods at high SNR values.
Electronics & Communications Engineering Department
MS in Electronics & Communication Engineering
Date of Award
Online Submission Date
Committee Member 1
Committee Member 2
Library of Congress Subject Heading 1
Wireless communication systems.
Library of Congress Subject Heading 2
Systems on a chip -- Design and construction.
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(2015).Low complexity blind and data-aided IQ imbalance compensation methods for low-IF receivers [Master’s thesis, the American University in Cairo]. AUC Knowledge Fountain.
Eissa, Mohamed Hussein. Low complexity blind and data-aided IQ imbalance compensation methods for low-IF receivers. 2015. American University in Cairo, Master's thesis. AUC Knowledge Fountain.