Blind Estimation Algorithms for I/Q Imbalance in Direct Down-conversion Receivers

TL;DR

This paper introduces a low-complexity blind estimation algorithm for I/Q imbalance parameters in direct down-conversion receivers, improving compensation accuracy and achieving ideal BER performance.

Contribution

It proposes a novel joint first and second order statistics method for blind I/Q imbalance estimation, reducing complexity compared to traditional Gaussian maximum likelihood approaches.

Findings

The proposed FSS-based algorithm effectively estimates I/Q imbalance parameters.

The FSCSM compensation method reaches the ideal BER performance.

Analysis reveals the cause of error floors in conventional compensation methods.

Abstract

As known, receivers with in-phase and quadrature phase (I/Q) down conversion, especially direct-conversion architectures, always suffer from I/Q imbalance. I/Q imbalance is caused by amplitude and phase mismatch between I/Q paths. The performance degradation resulting from I/Q imbalance can not be mitigated with simply higher signal to noise ratio (SNR). Thus, I/Q imbalance compensation in the digital domain is critical. There are two main contributions in this paper. Firstly, we proposed a blind estimation algorithm for I/Q imbalance parameters based on joint first and second order statistics (FSS) which has lower complexity than conventional Gaussian maximum likelihood estimation (GMLE). This can be used for further processing such as equalization in the presence of receiver IQ imbalance. In addition, we find out the reason of the error floor in conventional I/Q imbalance compensation method based on the conjugate signal model (CSM). The proposed joint first order statistics and conjugate signal model (FSCSM) compensation algorithm can reach the ideal bit error rate (BER) performance.