Channel estimation for OFDM systems using Kalman filter algorithm

Abstract

This paper presents the Kalman filter (KF) based channel estimation algorithm for orthogonal frequency division multiplexing (OFDM) systems. The cyclic prefix (CP) portion of the OFDM symbols is used for extracting the channel state information. The KF algorithm computes a channel estimate based on the information contained in the cyclic prefix. This channel estimation algorithm is compared with the classical least squares (LS) estimation approach. The simulation result shows that the KF algorithm outperforms then LS method. Absence of pilot signals and better adaptability to channel variations are other advantages of the KF method.