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Enhanced Spatial Covariance Matrix Estimation for Asynchronous Inter-Cell Interference Mitigation in MIMO-OFDMA System

To mitigate the asynchronous ICI (inter-cell interference), SCM (spatial covariance matrix) of the asynchronous ICI plus background noise should be accurately estimated for MIMO-OFDMA (multiple-input multiple-output-orthogonal frequency division multiple access) system. Generally, it is assumed that the SCM of the asynchronous ICI plus background noise is estimated by using training symbols. However, it is difficult to measure the interference statistics for a long time and training symbol is also not appropriate for MIMO-OFDMA system such as LTE (3GPP long term evolution). Therefore, a noise reduction method is required to improve the estimation accuracy. Although the conventional time-domain low-pass type weighting method can be effective for noise reduction, it causes significant estimation error due to the spectral leakage in practical OFDM system. Therefore, we propose a time-domain sine type weighing method which can not only reduce the noise effectively minimizing estimation error caused by the spectral leakage but also implement frequency-domain moving average filter easily. By using computer simulation, we show that the proposed method can provide up to 3 dB SIR (signal to interference ratio) gain compared with the conventional method, and verify that the proposed method is attractive and suitable for implementation with stable operation.