Deep Learning-Based Handover Prediction for 5G and Beyond Networks
JPSH Lima, ÁAM de Medeiros… - ICC 2023-IEEE …, 2023 - ieeexplore.ieee.org
Although the 5G New Radio standard empowers the mobile communication networks with
diverse technologies such as Massive MIMO, mmWave deployments, and much more, some …
diverse technologies such as Massive MIMO, mmWave deployments, and much more, some …
Deep-mobility: A deep learning approach for an efficient and reliable 5g handover
RA Paropkari, A Thantharate… - … Conference on Wireless …, 2022 - ieeexplore.ieee.org
5G cellular networks are being deployed all over the world and this architecture supports
ultra-dense network (UDN) deployment. Small cells have a very important role in providing …
ultra-dense network (UDN) deployment. Small cells have a very important role in providing …
Handover prediction integrated with service migration in 5g systems
As the research community inclines toward adopting increasingly complex techniques for
future networks, and simple methods are often ignored, being labeled as trivial. In this paper …
future networks, and simple methods are often ignored, being labeled as trivial. In this paper …
Predictive handover strategy in 6g and beyond: A deep and transfer learning approach
I Panitsas, A Mudvari, A Maatouk… - arXiv preprint arXiv …, 2024 - arxiv.org
Next-generation cellular networks will evolve into more complex and virtualized systems,
employing machine learning for enhanced optimization and leveraging higher frequency …
employing machine learning for enhanced optimization and leveraging higher frequency …
PBPHS: a profile-based predictive handover strategy for 5G networks
J Sun, Y Zhang, M Trik - Cybernetics and Systems, 2024 - Taylor & Francis
One of the necessities of mobile networks is uninterrupted access to wireless services,
taking into account the requirements of quality of service. With the development of the fifth …
taking into account the requirements of quality of service. With the development of the fifth …
A Low-Complexity Handover Scheme Using Unsupervised Learning Techniques for 6G Multi-Networking
In the emerging 6G era, a multi-networking archi-tecture is crucial to satisfy the growing
connectivity demands of resource-constrained loT devices. Additionally, employing higher …
connectivity demands of resource-constrained loT devices. Additionally, employing higher …
Enhancing Handover for 5G Mobile Networks using Jump Markov Linear System and Deep Reinforcement Learning
The fifth Generation (5G) mobile networks use millimeter Waves (mmWaves) to offer giga bit
data rates. However, unlike microwaves, mmWave links are prone to user and topographic …
data rates. However, unlike microwaves, mmWave links are prone to user and topographic …
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) …
namely, to reduce the number of handover failures by preparing target Base Stations (BSs) …
Prediction-based conditional handover for 5G mm-wave networks: A deep-learning approach
Conditional handover (CHO) is one of several promising mobility enhancements in 5G
networks. By making preparation decisions earlier than in LTE HO, CHO can provide an …
networks. By making preparation decisions earlier than in LTE HO, CHO can provide an …
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 …
on the use of artificial intelligence. We suggest using GRU recurrent neural networks, as …