An Improved Channel Estimation Algorithm for MIMO-OFDM Systems

The superior performance promised by multiple-input multiple-output (MIMO) antenna technologies relies on accurate channel state information (CSI) to be available at the receiver. This is particularly challenging when MIMO antenna is employed in conjunction with orthogonal frequency-division multiplexing (OFDM) modulation, and the channels are to be estimated in one OFDM symbol. The difficulty is that for each sub-carrier, there are more than one channels to be estimated, one for each transmit antenna, leading to an underdetermined system. Theoretically, perfect recovery of CSI is impossible even in the absence of noise as the number of unknowns is more than the number of observations. Nevertheless, knowing the fact that the channels are correlated in frequency, this paper devises an iterative algorithm to estimate the CSI at all sub-carriers from all of the antennas. Our proposed technique is inspired by the observation that a simple linear function can well approximate the channel variation in frequency and that permits us to have more CSI estimates than observations at the receiver. Simulation results illustrate that for a (2,1)¹ OFDM system with 128 subcarriers, the mean-square-error (MSE) in channel estimation can be made below 10^-7 for channels with root-mean-square (rms) delay spread of 150 nsec as compared to MSE of 10 _-3 for the conventional estimation method using orthogonal training sequences and a standard interpolation function