Estimation of Sparse Time Dispersive SIMO Channels with Common Support in Pilot Aided OFDM Systems Using Atomic Norm

We consider the problem of estimation of sparse time dispersive channels in pilot aided OFDM systems on Single Input Multiple Output (SIMO) channels, i.e. with a single transmit and multiple receive antennas. In such systems the channels are inherently continuous-time and sparse, and there is a common support of the channel coefficients of channels associated with different antennas, resulting from the same scatterer. To exploit these properties, we propose a new channel estimation algorithm that combines the atomic norm minimization of the Multiple Measurement Vector (MMV) model, the MUSIC and the least squares (LS) methods. The atomic norm minimization of the MMV model allows to exploit the common support assumption and the continuous-time nature of the channels, MUSIC allows for simple joint estimation of the delays corresponding to the same scatterer, and LS allows for estimation of the path gains. To evaluate the proposed algorithm, we compare its performance with the case when the common support assumption is not used.