Space-Based Control Node Placement for Joint Handover and Migration Delay Optimization in LEO Networks
TL;DR
A rolling-horizon migration-aware dynamic greedy control node placement algorithm (RH-MA-DGCNP) is proposed, which updates the CN placement and the affiliation between access-layer satellites and CNs at each reconfiguration epoch while jointly considering the handover delay and the migration delay caused by transferring control-affiliation states from previous serving CNs to new serving CNs.
Abstract
Low Earth Orbit (LEO) communication networks are an important component of non-terrestrial networks (NTNs) in sixth-generation (6G) communication systems. LEO satellites are characterized by low propagation delay and highly time-varying topology. Space-based mobility management can effectively reduce transmission delay; however, rapid network variation makes space-based control node deployment and reconfiguration difficult to model and solve. Focusing on dual-layer LEO Walker constellations, this paper investigates the joint optimization of control node deployment and dynamic reconfiguration, and formulates a 0–1 mixed-integer linear programming model with multiple practical constraints, aiming to minimize the total handover and migration delay. The model incorporates practical constraints such as the CN resource budget, unique management of access layer satellites, inter-layer reachability, feeder link connectivity, non-empty control node (CN) management, and onboard resource capacity. To support online deployment, we propose a rolling-horizon migration-aware dynamic greedy control node placement algorithm (RH-MA-DGCNP), which updates the CN placement and the affiliation between access-layer satellites and CNs at each reconfiguration epoch while jointly considering the handover delay and the migration delay caused by transferring control-affiliation states from previous serving CNs to new serving CNs. A comparison with exact current-epoch MILP solutions obtained by CPLEX on validation instances shows that RH-MA-DGCNP achieves small optimality gaps with shorter computation time. Simulation results show that RH-MA-DGCNP achieves the lowest mean handover delay among all benchmark schemes and the lowest cumulative total delay cost among the quasi-dynamic and dynamic benchmark schemes. The CDF of handover delay further indicates that RH-MA-DGCNP has a higher proportion of low-delay handover events and effectively suppresses extremely high-delay handover cases. Sensitivity analyses under different elevation angle thresholds and ground station deployments further show that RH-MA-DGCNP maintains its performance advantage over the benchmark schemes under different network settings.