60 GHz ultra-wideband channel estimation based on a cluster sparsity compressed sensing

The propagations of 60 GHz millimeter-wave system, which occupies an enormous operation bandwidth, are always known to be intensively dispersive. This may, in practice, pose great challenges to the estimation of channel state information. In this article, we investigated a promising compressed sensing (CS) algorithm and its practical applications in the channel estimations of emerging 60 GHz millimeter-wave communications. By fully considering the particular characteristics of 60 GHz propagations and further utilizing another kind of channel sparsity, i.e., the specific block cluster sparsity embodied by the identified multiple clusters, a novel cluster sparsity compressed sensing (CS-CS) algorithm is proposed subsequently. Based on the provided experimental simulations, the comprehensive analysis on both the classical regularized orthogonal matching pursuit algorithm and our newly designed CS-CS algorithm are conducted. As has been demonstrated, the proposed new algorithm indeed shows a much superior performance compared with the other existing methods, which may significantly reduce the reconstruction error and hence improve the precision of channel estimation. At the same time, the time complexity of signal reconstruction of the new CS-CS algorithm may be simplified to some extent.