Improving MIMO Channel Estimation Through Training Symbols Redundancy

Multiple input multiple output (MIMO) communication systems promise high channel capacity and data transmission rate. To obtain these characteristics, they rely on the precise knowledge of the channel state information (CSI). Several techniques are been used for channel estimation with different complexities. They vary from the conventional Least Squares (LS) method to more sophisticated ones, employing precoders and decoders. More recently another technique was developed based on the duality between symbol and channel estimation, which leads to higher accuracy than the previous techniques. In this work, the dualistic theory is expanded by taking advantage of the possibility of including extra rows in the estimated channel matrix, when precoders and decoders are used. The mean square error in the estimation process is then significantly reduced, despite some additional complexity. Simulation results validate the proposed approach.