and high complexity channel acquisition algorithms. In addition, a low peak-to-average power ratio (PAPR) for randomly generated pilot signals usually cannot be guaranteed. These drawbacks can be mitigated via proper design of the deterministic sensing matrices (see, e.g., [@Calderbank10Construction; @Strohmer12Measure] and references therein).

The main contributions of this paper are summarized as follows:

-   Based on a physically motivated channel model, we establish a relationship between the space-frequency domain channel covariance matrix (SFCCM) and the channel power angle-delay spectrum for massive MIMO-OFDM. We show that when the number of BS antennas is sufficiently large, the eigenvectors of the SFCCMs for different UTs tend to be equal, while the eigenvalues depend on the respective channel power angle-delay spectra, which reveals the channel sparsity in the angle-delay domain. Then we propose the angle-delay domain channel response matrix (ADCRM) and the corresponding angle-delay domain channel power matrix (ADCPM), which can model the massive MIMO-OFDM channel sparsity in the angle-delay domain, and are convenient for further analyses.

-   With the presented channel model, we propose APSP-based channel acquisition (APSP-CA) for massive MIMO-OFDM in TDD mode. For APSPs, equivalent channels for different UTs will experience corresponding cyclic shifts in the delay domain. Using this property, 