Kronecker compressed sensing for massive MIMO

Under sparse channel assumptions, channel state information for the massive MIMO uplink can be effectively estimated without sampling every antenna. Assuming orthogonal pilot signals and a uniform linear array, channel estimation is performed by leveraging sparsity in the spatial and pilot code domains to reconstruct the channel to all antennas. Using compressed sensing techniques, spatial resolution comparable to full array sampling can be achieved in the uniformly random, line of sight channel. Results of sampling from 25 percent of a 256 element massive MIMO array during the uplink piloting phase are presented. The per user bit error rate achieved by using compressed sensing and sparse recovery channel estimates exceeds that achieved with the least squares channel estimate by 5 dB for the same number of sampled antennas.

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