Blind Adaptive I/Q Imbalance Compensation Algorithms for Direct-Conversion Receivers

Abstract

Blind adaptive I/Q imbalance compensation has become more popular during the last decade due to its simplicity and need for no training data. In existing work, it has been pointed out that a statistical property of a signal, which is referred to as the properness condition, can be used for blind I/Q imbalance compensation. In this letter, the equi-absolute variance condition as well as the properness condition are used to propose two blind adaptive I/Q imbalance compensation algorithms based on the well-known LMS and RLS adaptation algorithms. The performances of the proposed algorithms are evaluated through simulations, and it is shown that the proposed algorithms provide nice convergence behaviors and high image rejections.