A Subspace Method for I/Q Imbalance Estimation in Low-IF Receivers

TL;DR

This paper introduces a data-aided subspace method for estimating I/Q imbalance in low-IF receivers, effectively handling unknown interference and channel conditions, and outperforming existing blind compensation techniques.

Contribution

A novel subspace-based approach for I/Q imbalance estimation in low-IF receivers that does not require interference or noise statistics, and handles unknown fading channels.

Findings

Outperforms existing blind IQI compensation methods.

Effective in presence of unknown interference and channel conditions.

Does not require prior knowledge of interference or noise statistics.

Abstract

In low-intermediate-frequency (low-IF) receivers, I/Q imbalance (IQI) causes interference on the desired signal from the blocker signal transmitted over the image frequencies. Conventional approaches for data-aided IQI estimation in zero-IF receivers are not applicable to low-IF receivers. In zero-IF receivers, IQI induces self-interference where the pilots of the image interference are completely identified. However, in low IF receivers, the image interference originates from a foreign signal whose training sequence timing and structure are neither known nor synchronized with the desired signal. We develop a data-aided subspace method for the estimation of IQI parameters in low-IF receivers in the presence of unknown fading channel. Our approach does not require the knowledge of the interference statistics, channel model nor noise statistics. Simulation results demonstrate the superiority of our approach over other blind IQI compensation approaches.