This paper, deals with H-infinity channel estimation technique for Orthogonal Frequency Division Multiplexing (OFDM) systems, in fading channel. Channel estimation is important for wireless applications because, in practical transmission scenario, channel correlation functions are either not known or cannot be easily estimated. It is therefore desirable to have an estimator which is robust to mismatches between the assumed and the actual channel correlation functions. The wireless channel has fading characteristics and its time varying nature adds additional cost to estimator design. A simplified Kalman filter is proposed which reduces the noise effects of the least square estimation. While the Kalman filtering algorithm requires the noise process to be zero mean besides the requirement to know the standard deviation of the noise process, H-infinity filtering algorithm makes no assumption about the noise and hence is said to be more robust in the wake of uncertainty. The proposed channel estimation algorithm is more robust in terms of model uncertainty and is more suitable for OFDM systems. Further, the complexity of the H-infinity filter is not too high. Given the conditions, H-infinity poses a suitable filter than any other, for channel estimation.

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