An enhanced whitening rotation semi-blind channel estimation for massive MIMO-OFDM

The efficient and highly accurate channel state information at the base station is essential to achieve the potential benefits of massive multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) systems, due to limitation of the pilot contamination problem. In this paper, we investigate the whitening rotation (WR) semi-blind channel estimation algorithm for multi-cell massive MIMO to address the pilot contamination problem through semi-blind approaches of hybrid scheme of pilot and blind to reduce the number of the required pilots. We also enhance the estimation accuracy by combining the proposed estimation technique with temporal domain based channel estimation, i.e., the conventional discrete Furrier transform (DFT) based channel estimator. It has shown that the performance of the WR semi blind estimator achieves a significantly lower Mean Square error (MSE) of estimation compared to the conventional linear minimum mean square error (LMMSE). Also, the proposed scheme of the combined DFT and WR semi blind estimator is seen to have a significantly superior performance compared to LMMSE and WR semi blind estimators.