A low complexity DFT-matrix based pilot allocation algorithm for sparse channel estimation in OFDM systems

The accuracy of channel estimation is very important for Orthogonal Frequency Division Multiplexing (OFDM) systems. In a high speed wideband wireless communication, the channel can be modeled as a sparse one. Therefore, the Compressed Sensing (CS) technique can be used for the estimation of the channel. In this paper, the problem of deterministic pilot allocation in OFDM systems is considered and a new criterion which is based on minimizing the summation of the correlations between the columns of the Discrete Fourier Transform (DFT) sub-matrix is proposed. It will be shown that the proposed criterion is a simple version of the well-known but complex criterion, Restricted Isometry Property (RIP). In addition, the pilot pattern design, using our proposed scheme, indicates better recovery performance than other proposed coherence based criteria in terms of the reconstruction mean square error (MSE) and successful channel recovery percentage. Simulation results confirm our analysis.