 when the main scattering appears close to the antenna arrays and has been validated by outdoor and indoor measure- ments. Assuming Rayleigh fading, the Kronecker model means that the channel matrix can be represented as = (R1/2) where the elements of Hchannel are independent and identically distributed as circular symmetric complex Gaussian random variables with zero- mean and unit variance. The important part of the model is that Hchannel is pre-multiplied by the receive-side spatial correlation matrix RRX and post-multiplied by transmit-side spatial cor- relation matrix RTX. Equivalently, the channel matrix can be expressed as H ~ C(0,RTX x RRX) where x denotes the Kronecker product [9]. Using the Kronecker model, the spatial correlation depends directly on the eigenvalue distri- butions of the correlation matrices RRX and RTX. Each eigenvector represents a spatial direc- tion of the channel and its corresponding eigenvalue describes the average channel/signal gain in that direction. For the transmit-side, the correlation matrix RTX describes the average gain in a spatial transmit direction, while receive-side correlation matrix RRX describes a spatial receive direction. High spatial correlation is represented by large eigenvalue spread in RTX or RRX, implying that some spatial directions are statistically stronger than the others. On the other hand, low spatial correlation is represented by small eigenvalue spread in RTX or RRX, which implies that almost the same signal gain can be expected from all spa- tial directions [9]. Let's now focus on a specific case of downlink transmission from a base station to a mobile station. Denoting the nth snapshot of the spatial correlation matrices at the gNB and the UE by RgNB,n and RUE,n, the per-tap spatial correlation is determined as the Kronecker product of the gNB and UE's antenna correlation matrices as Rn = RgNB,n X RUE,n. We denote the number of receive antennas by NRX and the number of transmit antennas by NTX. If Given a m X n matrix A and a pXq matrix B, the K