Structured Distributed Sparse Channel Estimation for High Mobility OFDM Systems

In high mobility environments, the significant Doppler shift introduces severe inter-carrier interference (ICI) to an orthogonal frequency-division multiplexing (OFDM) system, which makes channel estimation very challenging. In this paper, we propose an efficient structured distributed compressive sensing (SDCS) based joint channel estimation scheme within multiple OFDM symbols. By utilizing the complex exponential basis expansion model (CE-BEM) in the time domain and exploiting the channel sparsity in the delay domain, we obtain a joint-block-sparse model. Then a novel block-based simultaneous orthogonal matching pursuit (BSOMP) is proposed to make joint estimation of channel parameters accurately. Simulation results demonstrate that the proposed SDCS scheme achieves better channel estimation performance than the conventional CS and DCS scheme over high mobility channels.