Coverage Partitioning for Aerial Intelligent Reflecting Surface Phase Mapping Methods

This study proposes a novel aerial intelligent reflecting surface (IRS)-aided downlink communication framework to support user equipment (UE) in hotspot coverage areas. Aerial IRSs can establish additional line-of-sight links by bypassing ground blockages but incur high overhead due to channel estimation and control signaling. To reduce overhead while preserving the signal-to-noise ratio performance, we propose an IRS phase mapping method that leverages the geometric knowledge of hotspot coverage. This method involves two phases: i) an offline phase, which partitions the hotspot coverage into multiple disjoint regions and computes an optimal IRS phase-shift vector for each; and ii) an online phase, which maps the appropriate phase-shift vector to the UE based on its position. The generalized Lloyd algorithm is used in the offline phase to optimize the coverage partitions and corresponding IRS phase-shift vectors jointly. Numerical simulations validate the effectiveness of the proposed method, particularly when the UE's position information is known at the base station.