ML-based iterative channel and spatial covariance estimation in asynchronous interference environment for OFDMA system

To mitigate the asynchronous ICI (Inter-Cell Interference), the CFR (Channel Frequency Response) and SCM (Spatial Covariance Matrix) should be accurately estimated. Therefore, we propose the ML (Maximum Likelihood)-based iterative method which can effectively reduce the estimation error of both CFR and SCM, and improve the performance for OFDMA system such as LTE (3GPP Long Term Evolution).