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

We consider the problem of estimation of sparse time dispersive Single Input Multiple Output (SIMO) channels, using a single transmit and multiple receive antennas in pilot aided OFDM systems. The channels we consider are with a continuous time delays and sparse, and we assume a common support of the channel coefficients of the SIMO channels associated with different antennas, resulting from the same scatterer. To exploit these properties, we propose a new channel estimation algorithm based on the atomic norm minimization for the Multiple Measurement Vector (MMV) model. A joint estimation of the delays corresponding to the same scatterer is obtained using the combination of the atomic norm regularized minimization for the MMV model and the MUSIC method. Then, based on the availability of the channel correlation information, the path gains are estimated using the LS or the MMSE method. Additionally, we derive a theoretical estimate of the channel estimate Mean Square Error for the asymptotically increasing number of receive antennas. To evaluate the proposed algorithm, we compare its performance with other state of the art algorithms.