Performance of subspace based semi-blind channel estimation in MIMO systems

To meet the demand of high data rate transmission in multimedia century, the multiple-input multiple-output (MIMO) technique have been chosen as key solution in the advanced wireless communications. Generally, the training-based least square (LS) algorithm is considered as the simplest one for MIMO channel estimation. For resolving the bandwidth efficiency problem, we can combine the LS estimation with the pure blind techniques such as second-order statistics (SOS). In this investigation, we attempt to find the combined scheme which is so-called semi-blind channel estimation and outperforms than the conventional LS based approaches. Simulation results confirm our modified scheme and illustrate that the subspace based new semi-blind channel estimation is capable of improving the performance of the overall system.