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In order to take advantage of adaptive transmission techniques or multiple antennas, it is necessary to have actual channel state information (CSI) at transmitter and/or receiver. Due to system constraints and the time varying nature of the mobile radio channel, the CSI might be outdated, leading to performance degradation of the system. Channel prediction can provide up-to-date channel state information and reduce capacity loss. This paper presents a channel predictor based on the set-membership affine projection filtering involving an OFDM system. Realistic physical channel model used for standardization is considered to evaluate the performance of the predictor and compare it to well-known adaptive algorithms NLMS and RLS. Simulation results also show the bit-error rate performance and the robustness of the proposed predictor under the specifications of 3GPP Long Term Evolution (LTE).