Semi-blind channel estimation for MIMO/OFDM systems using superimposed training

This paper deals with the problem of channel estimation scheme for multiple-input multiple-output/ orthogonal frequency-division multiplexing (MIMO/OFDM) systems based on superimposed training (ST). Channel coefficients are firstly estimated by judicious designing superimposed pilot sequences across different users. Then, we derive a close-form expression for estimation variances. To further enhance the channel estimation performance, an iterative joint estimation algorithm with analytical performance analysis is provided to mitigate the interferences due to the unknown information sequences (thus to improve SER levels). Simulations show that with the iterative mitigation procedure, the demodulator exhibits a nearly indistinguishable performance from the OFDM systems of frequency-division multiplexed trainings.