Handover Optimization for IRS-Aided Networks With Experimental Verification

Signal fluctuations caused by blockage effects induce numerous handover failures (HOFs) and ping-pongs (PPs). Intelligent reflecting surfaces (IRSs) have the potential to address this issue by constructing indirect Line-of-Sight (LoS) links. However, this potential remains underexploited since existing works lack dedicated handover (HO) parameter optimization approaches. This paper proposes an HO boundary generation model for optimizing the HO parameters of IRS-aided networks, where the locations of HO events (HO triggers, HOFs, and PPs) are explicitly modeled as geometric boundaries reshaped by signal blocking and IRS reflection to evaluate and minimize HOFs and PPs. Specifically, initial boundaries are generated by projecting received signal strength trigger conditions for HO events onto the geometric elements across all considered propagation conditions. Exact boundaries are then determined by preserving parts of the geometric elements where the propagation condition holds. By evaluating the distance between the boundaries of HO events, the upper bounds on HOF and PP probabilities are derived and minimized under the worst-case criterion to determine the optimal HO parameters (HO offset and time-to-trigger). Simulations and IRS prototype-based experimental verifications are conducted to validate the proposed algorithm. Field measurements in a typical corridor corner scenario confirm that the IRS inherently reduces HOFs and PPs, and the proposed algorithm further reduces incorrect HOs by at least 42.2% compared to existing algorithms.