Downlink Precoding for DP-UPA FDD Massive MIMO via Multi-Dimensional Active Channel Sparsification

In this paper, we consider user selection and downlink precoding for an over-loaded single-cell massive multiple-input multiple-output (MIMO) system in frequency division duplexing (FDD) mode, where the base station is equipped with a dual-polarized uniform planar array (DP-UPA) serves large number of single-antenna users. Due to absence uplink-downlink channel reciprocity high-dimensionality matrices, it extremely challenging design precoders using closed-loop probing feedback limited spectrum resource. To address these issues, novel methodology – active sparsification (ACS) has been proposed recently literature linear (ULA) sparsifying precoders, which substantially reduces overhead. Pushing forward line research, aim facilitate potential deployment ACS practical FDD MIMO systems, by extending from ULA DP-UPA explicit making current implementation simplified. end, leveraging Toeplitz matrix theory, start spectral properties covariance matrices lens their matrix-valued density function. Inspired properties, extend original scalar-weight bipartite graph representation matrix-weight counterpart. Building upon such representation, propose multi-dimensional (MD-ACS) method, generalization formulation more suitable antenna configurations. The nonlinear integer program MD-ACS can be classified as generalized multi-assignment problem (GMAP), simple yet efficient greedy algorithm solve it. Simulation results demonstrate performance improvement over state-of-the-art methods based on QuaDRiGa models.