An AI-based optimization of handover strategy in non-terrestrial networks

C Zhang, N Zhang, W Cao, K Tian… - 2020 ITU Kaleidoscope …, 2020 - ieeexplore.ieee.org
A complicated radio resource management, eg, handover condition, will be suffered by the
user in non-terrestrial networks due to the impact of high mobility and hierarchical layouts …

Machine learning based handover execution algorithm for heterogeneous wireless networks

N Nayakwadi, R Fatima - 2020 Fifth International Conference …, 2020 - ieeexplore.ieee.org
Amalgamation of mmWave and LTE sub-6 provides an advantage in enhancing the
reliability, communication bandwidth and optimized coverage of intelligent network and its …

Efficient handover algorithm in 5G networks using deep learning

ZH Huang, YL Hsu, PK Chang… - GLOBECOM 2020-2020 …, 2020 - ieeexplore.ieee.org
In 5G networks, microcells are densely deployed for the spatial reuse to cooperate with the
traditional macrocells, and thus a moving user equipment (UE) usually experiences a more …

ECHO: Enhanced conditional handover boosted by trajectory prediction

A Prado, H Vijayaraghavan… - 2021 IEEE Global …, 2021 - ieeexplore.ieee.org
Conditional handover (CHO) has been introduced in 5G to improve mobility robustness,
namely, to reduce the number of handover failures by preparing target Base Stations (BSs) …

[引用][C] Deep learning with game theory assisted vertical handover optimization in a heterogeneous network

S Kayikci, N Unnisa, A Das, SKR Kanna… - … Journal on Artificial …, 2023 - World Scientific
Problem: In next-generation networks, users can optimize or tune their preferences with a
seamless transfer of diverse access methodologies for maximizing the Quality of Service …

Machine-learning-based predictive handover

A Masri, T Veijalainen, H Martikainen… - 2021 IFIP/IEEE …, 2021 - ieeexplore.ieee.org
Good mobility performance is critical in cellular networks for ensuring that each user is
always connected to the best possible cell and that the handovers are executed timely to …

Deep learning based adaptive handover optimization for ultra-dense 5G mobile networks

B Shubyn, N Lutsiv, O Syrotynskyi… - 2020 IEEE 15th …, 2020 - ieeexplore.ieee.org
An overview is devoted to the automation of fifth-generation mobile communications based
on the use of artificial intelligence. We suggest using GRU recurrent neural networks, as …

Intersystem handover decision model for heterogeneous wireless networks

TE Mathonsi, OP Kogeda… - 2018 Open Innovations …, 2018 - ieeexplore.ieee.org
The number of mobile users has exponentially grown over the past years, and these users
have the desire of always being connected wirelessly at any time anywhere, to the best …

Handover performance improvement in heterogeneous wireless network

NA Ezz-Eldien, MF Abdelkader… - 2020 11th IEEE …, 2020 - ieeexplore.ieee.org
Moving to the next generations of mobile networks means to deal with multi-heterogeneous
network dense deployment as there will be no single network type capable of meeting all the …

A handover strategy based on user dynamic preference for LEO satellite

YH Lei, LF Cao, M Da Han - 2021 7th International Conference …, 2021 - ieeexplore.ieee.org
In the existing LEO satellite handover strategy, most of the indicators of handover decision
consider satellite network parameters rather than the actual requirements of user services …