Improved common correlation matrix based SMI algorithm by channel estimation error minimization with LMS approach

Abstract

This paper improves interference suppression performance of Common Correlation Matrix (CCM) based Sample Matrix Inversion (SMI) adaptive array antenna algorithm. Assuming multicarrier systems such as orthogonal frequency division multiplexing (OFDM), CCM is effective means to achieve good convergence of covariance matrix by utilizing time-domain signal samples before multicarrier conversion. However, the number of pilot symbols is still limited and receiver noise causes poor channel identification. Such inaccurate CSI estimation deteriorates the interference suppression performance of the CCM-SMI algorithm. The key proposal is introducing a minimization of channel estimation error using least mean square (LMS) approach. Computer simulation results verify the improved Bit Error Rate (BER) performance provided by a modified CCM-SMI algorithm.