  This study proposes an adaptive experimental design framework for channel
simulation-based base station (BS) design that supports joint optimization of
transmission power and placement. We consider a system in which multiple
transmitters provide wireless services over a shared frequency band. Our
objective is to maximize the average throughput within an area of interest.
System operators can design the system parameters prior to deployment by
iterating through channel simulations and updating parameters. However,
accurate channel simulations are computationally expensive, thus it is
preferable to configure the system using a limited number of simulation
iterations. We develop a solver for this problem based on Bayesian optimization
(BO), a black-box optimization method. Numerical results demonstrate that our
proposed framework can achieve 18-22% higher throughput performance compared to
conventional placement and power optimization strategies.
