An Efficient Pilot Design Scheme for Sparse Channel Estimation in OFDM Systems

This paper investigates the pilot placement problem for sparse channel estimation in orthogonal frequency division multiplexing (OFDM) systems. Prompted by the success of the compressed sensing technique in recovering sparse signals from undersampled measurements, compressed sensing has been successfully applied for pilot-aided sparse channel estimation in OFDM systems to reduce the transmitted overhead. However, the selection of pilot tones significantly affects channel estimation performance. Seeking optimal pilot placement for sparse channel estimation, in the sense of minimum mean-square error of the channel estimation, through an exhaustive search of all possible pilot placements is extremely computationally intensive. To reduce the computational complexity and simultaneously maximize the accuracy of sparse channel estimation, cross-entropy optimization is introduced to determine the optimal pilot placement. Computer simulation results demonstrate that the pilot index sequences obtained using the proposed method performed better compared with those obtained using the conventional equispaced scheme and the random search method.