VERTICAL HANDOVER DELAY MINIMIZATION IN NON-TERRESTRIAL NETWORKS: A REVIEW AND THE ATELES TIME-ADAPTIVE SEARCH FRAMEWORK

This review has examined the state-of-the-art in vertical handover (VHO) optimization for non-terrestrial networks (NTNs), emphasizing the challenges of LEO/vLEO constellations and 5G–6G mobility management. Existing approaches—spanning metaheuristics, machine learning, reinforcement learning, and protocol-level enhancements—offer partial improvements but remain constrained by computational complexity, dataset dependence, and limited adaptability to dynamic NTN topologies. To address these gaps, the Ateles Time-Adaptive Search (TAS) framework is proposed as a lightweight, adaptive strategy that dynamically tunes search intensity and timers, while differentiating between transparent and regenerative payload architectures. TAS centralizes predictive resource allocation in transparent payloads and leverages edge–coordinator cooperation in regenerative payloads to reduce latency and improve resilience. Despite its promise, TAS remains conceptual; key challenges persist in scalability, Doppler mitigation, multi-connectivity, synchronization, energy efficiency, and standardization. Future research must pursue implementation through simulations, hybrid emulators, and testbeds to advance TAS toward practical, deployable NTN mobility solutions.

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