A Compressed CSI Estimation Approach for FDD Massive MIMO Systems

To fully achieve the spectral and energy efficiency intended in large-scale antenna systems, acquiring the Channel State Information (CSI) is inevitable at the base station (BS) side. Due to the massive array at the BS side and large number of required pilots accordingly, acquisition of the channel can be challenging when the system is implemented in frequency-division duplex (FDD) protocol. In this paper, we introduce a novel compressive sensing (CS) algorithm which takes the advantages of correlation between the received and transmitted signals into account for an iterative estimation. For this purpose, we use the intersection among paired users and then select those who minimize the residual norm while the number of non-zero elements are also minimum. Simulation results indicates that the proposed algorithm outperforms other existing solutions and is able to approach the performance bound.