Group sparse estimation of time-varying delay OFDM channels based on compressed sensing

Time-varying delay fading of propagating channels degrades the performance of orthogonal frequency-division multiplexing (OFDM) systems. The theory of compressed sensing (CS) shows that sparse channels in high-dimensional spaces can be recovered from a relatively small number of samples. However, existing CS-based channel estimations require the sparsity as a prior for exact recovery. The sparsity of time-varying delay channels could not be well-defined. In this paper, a group sparse estimation of time-varying delay OFDM channels without prior information of the sparsity based on CS is given. The simulation results show that the new channel estimator can provide a considerable performance improvement in estimating time-varying delay channels, especially for the rapidly time-varying channels of a large Doppler frequency.