Structured Compressed Sensing of Double Selective Channel for High-Frequency OFDM Systems

In order to realize the real-time acquisition of the state information of the double selective channel with low pilot cost, a structured compressed sensing (SCS) based channel estimation method is proposed for high-frequency (HF) in this paper. Combining with the transmission model and sky wave channel model of HF OFDM systems, the channel estimation problem is formulated under the framework of compressed sensing. The block-structured sparsity of channel coefficients in transformed domain of double selective sky wave channel is proved. On this basis, the channel coefficients are reconstructed by structured compressed sensing algorithm. Simulation results show that the proposed structured compression sensing method can significantly reduce the pilot overhead and ensure the accuracy of channel estimation.