Abstract
The channel estimation methods track and predict the variation in channel characteristics, so that the original signal can be obtained after nullifying the channel induced influences. The channel estimation methods impact the overall performance of the MIMO-OFDM system. When the communicating nodes are mobile, a complete estimation of the fast time varying channel is accomplished if the Doppler offset is evaluated along with the channel gain. However, most of the channel estimation approaches proposed in literature for MIMO-OFDM systems assume that the Doppler offset contributed by highly mobile communicating nodes is already known to the receiver. The estimation of the Doppler offset with the channel coefficients renders the channel estimation problem non linear. In this paper, the issue of this non linear channel estimation for high mobility communicating nodes with associated dynamic Doppler offset in a MIMO-OFDM system is addressed. In order to obtain complete information of the channel which includes the channel coefficients and the associated Doppler offsets, a hybrid interval type-2 fuzzy aided Kalman filter for channel estimation is proposed. The type-2 fuzzy based membership functions are used here opposed to the type-1 fuzzy membership functions because the type-2 fuzzy membership functions are capable of effective modeling even under high degree of uncertainties. Furthermore, a detailed computational complexity analysis of the proposed algorithm is presented which shows that the algorithm has moderate computational complexity and has good performance in fast time varying channel conditions with high node mobility in a MIMO-OFDM system.
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