A bandwidth efficient channel estimation method using superimposed training for MIMO-OFDM systems

In this work an iterative time domain Least Squares (LS) based channel estimation method using superimposed training (ST) for a Multi Input Multi Output(MIMO) Orthogonal Frequency Division Multiplexing (OFDM) system over frequency selective fading channels is proposed. The estimate of the channel is generalized to provide scope for exploiting the coherence time and the coherence bandwidth for an improved performance. The performance of the channel estimator is analyzed in terms of the Mean Square Estimation Error (MSEE) and its impact on the uncoded Bit Error Rate (BER) of the MIMO-OFDM system is studied by considering a two branch transmitter diversity system employing Alamouti space time coding. The selection criterion for the training sequences is proposed by jointly optimizing the MSEE and the BER of the OFDM system. Such sequences, one for each transmitting antenna are required to form an orthogonal set and also ensure a fair distribution of the residual interference due to the training sequence on the data symbols prior to data detection in all the used subcarriers. The effectiveness of the mathematical analysis presented is demonstrated through a comparison with the simulation studies. Also, the proposed scheme is applied to the IEEE 802.16e OFDM standard, its suitability is examined and a case is made with the required design of the sequence.