Year: 2025
Type: conference-paper
Abstract: Low Earth Orbit (LEO) satellites exhibit high mobility, leading to frequent handover challenges. Addressing these handover issues is crucial for maintaining seamless and stable service connections. This paper presents a novel D1 event handover scheme that integrates Kalman filtering with artificial neural networks(ANN) to enhance handover performance in Non-Terrestrial Networks (NTN). In the proposed method, Kalman filtering provides precise UE position estimates and generates smooth trajectory predictions, which serve as inputs to a neural network. The neural network adaptively adjusts handover parameters (hysteresis and threshold) and intelligently selects the optimal target cell based on predicted positions, signal-to-interference-plus-noise ratio (SINR) and network load. Through modelling and simulation experiments, we demonstrate that the proposed scheme significantly reduces handover failure rates and ping-pong events. The results show that, compared to traditional D1 handover mechanisms and RSRP-based handover methods, the proposed scheme improves handover stability and reliability, offering an effective solution for intelligent mobility management in dynamic NTN environments.
Authors: Li-Sheng Chen, Shu-Han Liao
Institutions: National Ilan University, Tamkang University
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4408042320