The availability of large bandwidth at millimeter wave (mmWave) frequenciesis one of the major factors that rendered very high frequencies a promisingcandidate enabler for fifth generation (5G) mobile communication networks. Toconfront with the intrinsic characteristics of signal propagation atfrequencies of tens of GHz and being able to achieve data rates of the order ofgigabits per second, mmWave systems are expected to employ large antenna arraysthat implement highly directional beamforming. In this paper, we considermmWave wireless systems comprising of nodes equipped with large antenna arraysand being capable of performing hybrid analog and digital (A/D) processing.Intending at realizing channel-aware transmit and receive beamforming, we focuson designing low complexity compressed sensing channel estimation. Inparticular, by adopting a temporally correlated mmWave channel model, wepresent two compressed sensing algorithms that exploit the temporal correlationto reduce the complexity of sparse channel estimation, one being greedy and theother one being iterative. Our representative performance evaluation resultsoffer useful insights on the interplay among some system and operationparameters, and the accuracy of channel estimation.
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