Pilot Design and AMP-Based Channel Estimation for Massive MIMO-OFDM Uplink Transmission

This paper investigates the pilot design and channel estimation issue for massive MIMO-OFDM uplink transmission. By exploiting the channel sparsity in the beam-delay domain, the channel estimation issue for multiuser uplink transmission is formed into a sparse compressed sensing (CS) model. We propose a cyclic shift pilot scheme, which satisfies Restricted Isometry Property under the CS frameworks. As the sparsity is efficiently utilized, the proposed scheme significantly reduces the pilot overhead, especially when the number of users becomes large. Furthermore, based on approximate message passing (AMP) algorithm, an approximate Bayesian inference can be conducted for channel estimation with low complexity. Simulation results show that the proposed AMP-based algorithm with the pilot scheme outperforms several existing baselines, especially when the BS is equipped with large antenna arrays.