Machine learning-based handover failure prediction model for handover success rate improvement in 5g
This paper presents and evaluates a simple but effective approach for substantially reducing
inter-frequency handover (HO) failure rate. We build a machine learning model to forecast …
inter-frequency handover (HO) failure rate. We build a machine learning model to forecast …
A data-driven framework for inter-frequency handover failure prediction and mitigation
With 5G already deployed, challenges related to handover exacerbate due to the dense
base station deployment operating on a motley of frequencies. In this paper, we present and …
base station deployment operating on a motley of frequencies. In this paper, we present and …
Novel algorithm to reduce handover failure rate in 5G networks
V Mishra, D Das, NN Singh - 2020 IEEE 3rd 5G World Forum …, 2020 - ieeexplore.ieee.org
Ultra-reliable low latency communication (URLLC) is a key feature in 5G which requires
improved mobility performance and reliability. In future, the number of devices are going to …
improved mobility performance and reliability. In future, the number of devices are going to …
[HTML][HTML] A Comprehensive Survey on Machine Learning Methods for Handover Optimization in 5G Networks
One of the key features of mobile networks in this age of mobile communication is seamless
communication. Handover (HO) is a critical component of next-generation (NG) cellular …
communication. Handover (HO) is a critical component of next-generation (NG) cellular …
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 …
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 …
Intelligent handover decision scheme using double deep reinforcement learning
Handovers (HOs) have been envisioned to be more challenging in 5G networks due to the
inclusion of millimetre wave (mm-wave) frequencies, resulting in more intense base station …
inclusion of millimetre wave (mm-wave) frequencies, resulting in more intense base station …
Novel technique in 4G Handover parameter tuning and prediction using statistical trend analysis and supervised machine learning
T Elmahdy, AF Bendary - 2021 International Symposium on …, 2021 - ieeexplore.ieee.org
This paper displays a novel technique that allows tuning and predicting better values for A3
offset handover parameter for both inter-frequency and intra-frequency. The proposed work …
offset handover parameter for both inter-frequency and intra-frequency. The proposed work …
Machine learning aided holistic handover optimization for emerging networks
In the wake of network densification and multi-band operation in emerging cellular networks,
mobility and handover management is becoming a major bottleneck. The problem is further …
mobility and handover management is becoming a major bottleneck. The problem is further …
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 …