Robust low-complexity joint space–time–frequency channel estimation with transmit diversity in mobile wireless channels

In this paper, a robust low-complexity joint space–time–frequency channel estimation with transmit diversity in mobile wireless channels is proposed. Based on the orthogonal frequency division multiplexing (OFDM), the previously known training sequences are firstly blocked, space–frequency complex orthogonally encoded, up-converted and transmitted with diversity in the transmitter. In the receive end, each subchannel frequency response is estimated directly through the inverse pilot space–frequency complex orthogonally decoding. Wiener filtering and interpolating with the time- and frequency-domain correlations of the frequency response of the mobile wireless channels, low-complexity joint space–time–frequency channel estimator is finally constructed. In our proposed scheme, the high-level large-scale matrix inverse operations in traditional multiple input multiple output (MIMO) channel estimations are avoided. Separate and independent channel estimation corresponding to each pair of transmit and receive antennas in the MIMO space–frequency block coding system is achieved with transmit diversity, which can be used to significantly reduce the computation complexity with no degradation in system performance. Moreover, to successfully decoding the known pilot subblock coding matrix, it is only required that the fading channel keep approximately constant in each space–frequency coding subblock during one OFDM symbol block period. Making full use of the best time- and frequency-domain filtering, it makes our proposed scheme even more robust and accurate to estimate and track the channels with rapid time-varying dispersive fading. Numerical results are provided to validate the performance of our proposed channel estimators with diversity in mobile wireless channels.