Abstract
Direct-conversion transceivers are the predominating architecture in current mobile communication systems. Despite many advantages, this topology suffers from unavoidable mismatches in the analog part, which causes imbalance between the in-phase and quadrature (I/Q) component. In this paper, we present a novel fully digital, blind I/Q imbalance compensation algorithm that features extremely low computational complexity and high compensation performance for a wide range of input signal types. Different to many state-of-the-art compensation schemes, the approach is not based on a gradient descent optimization and does not require any global feedback. This simplifies the implementation at high data rates and reduces the configuration effort to a minimum. For comparison, we examine an existing method of moment-based estimator with similar properties, for which we also provide the detailed insights beyond available literature. For both algorithms, we provide a rigorous mathematical analysis, which is supported by simulations with a focus on various long-term evolution (LTE) signal types. In addition, hardware architectures, including field-programmable gate array (FPGA) verification, are presented for both algorithms.
Highlights
C URRENT radio frequency (RF) transceivers implementing mobile communication standards such as Long-Term Evolution (LTE) usually employ the direct-conversion architecture
We examine the special case of |α| = 1, where the exact solution can be obtained from a single sample at an arbitrarily chosen time index n: y[n] y[n]∗
We presented a novel blind ultra-low complexity algorithm for in-phase and quadrature (I/Q) imbalance compensation in direct-conversion transceivers
Summary
C URRENT radio frequency (RF) transceivers implementing mobile communication standards such as Long-Term Evolution (LTE) usually employ the direct-conversion architecture. This results in a spectral image compromising the quality of the received signal which can be quantized by the so-called image rejection ratio (IRR) [1]–[6]. Many blind algorithms use adaptive filtering methods [14], [15] This typically leads to imbalance cancellation schemes that solve quadratic cost functions using a gradient descent approach [16]–[18]. These algorithms feature low complexity, many of them require a feedback loop, which complicates the digital design or the integration in a multi standard digital-front end (DFE). The frequency dependent variations of the imbalance are usually low, which allows an approximation by a finite impulse response (FIR) filter with only a few coefficients [26]
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE Transactions on Circuits and Systems I: Regular Papers
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
