Linear Least Squares CFO Estimation and Kalman Filtering Based I/Q Imbalance Compensation in MIMO SC-FDE Systems

This paper investigates carrier frequency offset (CFO) estimation and inphase/quadrature (I/Q) imbalance compensation in time-varying frequency-selective channels. We first propose a linear least squares (LLS) CFO estimation approach which has a lower complexity and a higher accuracy than the previous nonlinear CFO estimation methods. We then propose a Kalman filtering based I/Q imbalance compensation approach in the presence of CFO, which demonstrates a good ability to track the channel time variations with a fast convergence speed, by nulling the cyclic prefix (CP) and including the CFO in the state vector of the equivalent channel model. The proposed Kalman filtering based I/Q imbalance compensation approach with associated equalization tracks the time variation with a fast convergence speed. Simulation results show that the proposed compensation approach for CFO and I/Q imbalance provides a bit error rate (BER) performance close to the ideal case with perfect channel state information (CSI), no CFO and no I/Q imbalance.