Kadir Has University
This paper is concerned with a challenging problem of channel estimation for amplify-and-forward cooperative relay based Orthogonal Frequency Division Multiplexing (OFDM) systems in the presence of sparse underwater acoustic channels and of the correlative non-Gaussian noise. The authors exploit the sparse structure of the channel impulse response to improve the performance of the channel estimation algorithm, due to the reduced number of taps to be estimated. The resulting novel algorithm initially estimates the overall sparse channel taps from the source to the destination as well as their locations using the Matching Pursuit (MP) approach. The correlated non-Gaussian effective noise is modeled as a Gaussian mixture.