Data detection and soft-Kalman filter based semi-blind channel estimation algorithms for MIMO-OFDM systems

In MIMO systems, where multiple antennas are used at both transmitter and receiver to achieve high spectral efficiency, channel impulse responses are often assumed to be constant over a block or packet. This assumption of block stationarity on channels is valid for most fixed wireless scenarios. However, for communications in a high mobility environment, the assumption will result in considerable performance degradation. In this paper, we focus on channel estimation for a MIMO system with OFDM transmission technique. In our system, pilots are placed on subcarriers for a novel channel estimation at the receiver with Kalman filters. With the channels estimated by a Kalman filter, we apply the OFDM MIMO soft data detector with a reasonable computational cost. The soft outputs of soft data detection are fed back to another soft Kalman filter for an improved channel estimation. By alternatively and iteratively using these two Kalman filters, a better overall performance can be obtained.