Joint Estimation of Transmitter and Receiver IQ Imbalance With ML Detection for Alamouti OFDM Systems

The application of multiple transmit antennas in orthogonal frequency-division multiplexing (OFDM) systems provides better spectral efficiency with high performance gain. However, these systems are very sensitive to channel estimation errors and analog front-end impairments, such as in-phase/quadrature-phase (IQ) imbalance. To ensure a reliable transmission, the channel impulse response (CIR) and IQ imbalance have to be accurately estimated. Unlike previous work, we show that the unwanted IQ imbalance can be exploited to achieve a diversity gain. This paper develops a maximum-likelihood (ML) detector by exploiting the diversity gain resulting from the IQ imbalance for Alamouti space-time block code OFDM systems. Moreover, we propose a novel iterative algorithm to jointly estimate the CIR and IQ imbalance occurring at both the transmitter and the receiver. We initially employ a pilot sequence for estimation and detection. Then, we exploit the soft information provided by the detector via an expectation-maximization (EM) algorithm to improve the estimation efficiency iteratively. To reduce the computational complexity of the estimation process, a suboptimal algorithm is also developed. Simulation results indicate that the bit-error-rate (BER) performance of the proposed detector in conjunction with the proposed estimation algorithms is very close to the BER of the perfectly known parameters case with a diversity gain resulting from the IQ imbalance.