An Iterative Channel Estimation Method using Superimposed Training in OFDM Systems

In this work an iterative time domain Least Squares (LS) based channel estimation method using superimposed training (ST) for an Orthogonal Frequency Division Multiplexing (OFDM) system over frequency selective fading channels is proposed for the IEEE 802.16e2005 standard. 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 OFDM system is studied. The selection criterion for the training sequences is proposed by jointly optimizing the MSEE and the BER of the OFDM system. Such a sequence is required to have an impulse like autocorrelation for lags extending atleast upto the order of the estimator 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 standard, its suitability is examined and a case is made with the required design of the sequence.