Abstract:
This paper studies the problem of time-varying and sparse channel estimation in the orthogonal frequency division multiplexing (OFDM) system. The complex exponential-basis expansion model (CE-BEM) is used to model the time-varying channel's response. The coefficient in CE-BEM is sparse due to the channel's sparsity. Thus, the problem of estimating the sparse channel response turns into solving the coefficient of sparse CE-BEM. For the scene with unknown sparsity, this paper proposes a sparsity adaptive distributed compressive sensing algorithm. Furthermore, a pilot pattern design method is given to deal with the effect of pilot placement on channel estimation. Finally, the simulation results show that the proposed algorithm can effectively improve estimating performance.