Low Complexity Channel Estimation for ISDB-T using Modified Orthogonal Matching Pursuit

Ryan Paderna (1351123)

We proposed a new scheme for compressed sensing based channel estimation for ISDB-T using Modified Orthogonal Matching Pursuit. The proposed system uses a time domain approach which took the advantage of the sparsity of impulse response. The system was able to reduce the complexity in estimating the channel since time domain calculation has less parameters.

In addition, the proposed scheme gives robustness against fractional delay by using oversampling. Numeral results shows that the proposed scheme has better performance compared to the conventional estimation. Moreover, computational complexity was maintained low even though oversampling was implemented.