MILP-Based Optimal Handover Decisions: A Benchmark for Mobility Management Algorithms

With the growing use of autonomous vehicles and autonomous aerial vehicles (AAVs), the requirements for reliable and seamless mobility in mobile networks are increasing. Although many handover optimization methods have been proposed, fair comparison is difficult because they rely on differing assumptions and there is no common benchmark. Therefore, it remains unclear how much optimization potential remains. We present a genie-aided benchmark based on mixed-integer linear programming (MILP) that uses precomputed signal quality to determine optimal handover decisions for given user trajectories in arbitrary network layouts. The framework captures key mobility mechanisms, including handover interruptions and radio link failures, and quantifies how far practical algorithms operate from the achievable performance limit.