Structured Compressed Sensing for Channel Estimation under High-Speed Mobile Environment

Abstract

In the fourth generation wireless communication systems, channel estimation technology is very important for orthogonal frequency division multiplexing (OFDM). However, the existing schemes hardly meet the demand for Quality of Service in high-speed mobile environment. To handle this problem, in this paper, the channel sparsity characteristic and temporal correlations are exploited and displayed by the block-sparse system model. Then, the block-based orthogonal matching pursuit (OMP) algorithm is used to obtain the channel state information. Simulation results illustrate the performance of our proposed algorithm superiority.