Algorithm 1 Alternating optimization algorithm based on SCA.

1. Initialize Set $\beta =0.6$ and the initial beamforming matrix ${\mathbf{F}}_s=\sqrt{\frac{p_s}{M_s}}{\mathbf{I}}_{M_s}$, ${\mathbf{F}}_r=\sqrt{\frac{p_r}{\mathrm{Tr}\left(\mathbf{R}\right)}}{\mathbf{I}}_{M_r}$. 2. Repeat (1) Update ${\mathbf{F}}_r$, w.r.t. ${\mathbf{F}}_s$, ${\mathbf{W}}_d$. Set $k_r=0$ and the initial center point ${\mathbf{z}}_r^0=vec\left({\mathbf{F}}_r\right)$. Solve problem Equation (22) at the $k_r$-th iteration to obtain ${\mathbf{F}}_r^{k_r}$ when $k_r\ge 0$. Then, set ${\mathbf{z}}_r^{k_r+1}=vec\left({\mathbf{F}}_r^{k_r}\right)$ and $k_r=k_r+1$. Until ${\parallel {\mathbf{z}}_r^{k_r+1}-{\mathbf{z}}_r^{k_r}\parallel }^2\le {10}^{-4}$, and let ${\mathbf{F}}_r=mat\left({\mathbf{z}}_r^{k_r+1}\right)$. (2)Update ${\mathbf{F}}_s$ with $k_s$ iterations, w.r.t. ${\mathbf{F}}_r$, ${\mathbf{W}}_d$, following similar steps to those in (1). (3)Update ${\mathbf{W}}_d$, w.r.t. ${\mathbf{F}}_r$, ${\mathbf{F}}_s$. 3. Until $▵MSE\le \delta$ or $iter\ge ite{r}_{max}$