Channel estimation for WiMaX systems using fuzzy logic cognitive radio

This paper proposes a cognitive radio approach for WiMAX (CogMAX). The proposed system has all the capabilities of cognitive radio from monitoring to action, decision and learning. We use fuzzy logic (FL) reasoning as the core of the reasoning engine. The reasoning engine is used to determine different parameters that will be used by the WiMAX system. This work will focus on one of the main functions of the reasoning engine i.e. determination of the channel type and the number of pilots used for channel estimation. The number of pilots will depend on the type of channel which is determined by the cognitive engine. We examine two channel estimators, the least square (LS) and the linear minimum mean square error (LMMSE) along with 2D-Linear, averaging and constant coefficients interpolators. Evaluation is done using the minimum square error with the SNR of the channel. Numerical results reveal that changing the number of pilots can lead to better channel estimation.