we ignore the estimation error during parameter optimization, while the effect of estimation error will be taken into account in the simulations. Let $\boldsymbol{p}^{\star}$ and $\bar{\boldsymbol{\phi}}^{\star}$ denote the set of optimal transmit power allocation and IRS reflection coefficients, respectively. The details on how to obtain $\boldsymbol{p}^{\star}$ and $\bar{\boldsymbol{\phi}}^{\star}$ will be presented in Section \[sec:pfsol\]. Afterwards, the BS feeds back $\boldsymbol{p}^{\star}$ to the user and $\bar{\boldsymbol{\phi}}^{\star}$ to the IRS controller, respectively.

Data Transmission
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Finally, with the optimized transmit power allocation $\boldsymbol{p}^{\star}$ available at both the BS and the user as well as the optimized IRS group reflection coefficients $\bar{\boldsymbol{\phi}}^{\star}$ available at the BS and the IRS, all IRS elements are switched on and data transmission proceeds with the optimized design parameters. Note that due to the presence of channel estimation error, which can be viewed equivalently as additional interference at the receiver, the achievable rate for actual data transmission will be lower than that obtained in . Furthermore, it is worth noting that there exists a fundamental *trade-off* between the training overhead versus the IRS reflection coefficient design flexibility. Specifically, as the number of groups $K$ and consequently the grouping ratio $\rho$ decreases, the estimation error decreases while the effective 