Sparse channel estimation using orthogonal matching pursuit in frequency domain

Accurate channel estimation is a necessary condition for data demodulation in wireless communication systems. Compared to traditional channel estimation method, compressed sensing theory can take full use of the sparse characteristics of the channel. The contradiction between channel estimation error and message rate can be effectively solved. Based on a system model of Single-antenna orthogonal frequency division multiplexing transmission, the performance of compressed sensing to channel estimation is studied. When Orthogonal Matching Pursuit Algorithm in frequency domain is used to sparse channel estimation, the accuracy of the channel estimation is greatly improved although the complexity of the algorithm is increased.