data transmission time increases, while the reduced number of elements in $\bar{\boldsymbol{\phi}}$ leads to less flexibility in the IRS reflection coefficient design and thereby potentially smaller achievable rate in the data transmission phase. Nevertheless, as the channel correlation among the IRS elements in the same group becomes stronger, it is anticipated that such design flexibility loss will be compensated by the saved data transmission time. Moreover, the optimal grouping ratio is also dependent on the channel coherence time. A comprehensive illustration of this trade-off will be given later in Section \[sec:sim\] via numerical results.

Achievable Rate Maximization via Joint Power Allocation and Reflection Coefficient Optimization {#sec:pfsol}
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Problem Formulation
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Based on the transmission protocol proposed in Section \[sec:ce\] as well as given IRS elements grouping $K$ and channel estimates $\hat{\boldsymbol{h}}_d$ and $\hat{\boldsymbol{V}}'$, we aim to maximize the achievable rate shown in (\[eqn:r2\]) by jointly optimizing the transmit power allocation and the IRS reflection coefficients. Therefore, we formulate the following optimization problem (by omitting the constant terms in (\[eqn:r2\]) for brevity) $$\begin{aligned}
\mathrm{(P1)}:\mathop{\mathtt{maximize~~}}_{\boldsymbol{p},\bar{\boldsymbol{\phi}}~}  &~~\sum_{n=0}^{N-1} \log_2\left(1\!+\!\frac{\left|\boldsymbol{f}_n^H\hat{\boldsymbol{h}}_{d}\!+\!\boldsymbol{f}_n^H\hat{\boldsymbol{V}}'\bar{\boldsymbol{\phi}}\right|^2p_n}{\Gamma\sigma^2} \right)  \nonumber\\
    \mathtt{subject\; to}
&~~\sum_{n=0}^{N-1} p_{n}\leq P, \label{eqn:const1}\\
&~~p_n \geq0, \quad \forall n \in \mathcal{N}, \label{eqn:const2}\\
&~~|\bar{\phi}_k|\leq 1, \quad \forall k\in \mathcal{K}.\label{eqn:const3}\end{aligned}$$ Problem (P1) is 