Double deep reinforcement learning assisted handovers in 5g and beyond cellular networks
In 5G and beyond cellular networks, the typical cell size has been reducing to provide higher
data rates and meet the low latency requirements. Such ultra-dense deployments of base …
data rates and meet the low latency requirements. Such ultra-dense deployments of base …
A Deep Reinforcement Learning-based Approach for Adaptive Handover Protocols in Mobile Networks
Due to an ever-increasing number of participants and new areas of application, the
demands on mobile communications systems are continually increasing. In order to deliver …
demands on mobile communications systems are continually increasing. In order to deliver …
State Aware‐Based Prioritized Experience Replay for Handover Decision in 5G Ultradense Networks
DF Wu, C Huang, Y Yin, S Huang… - Wireless …, 2022 - Wiley Online Library
The traditional handover decision methods depend on the handover threshold and
measurement reports, which cannot efficiently resolve the frequent handover issue and ping …
measurement reports, which cannot efficiently resolve the frequent handover issue and ping …
Optimization of cell individual offset for handover of flying base stations and users
A Madelkhanova, Z Becvar… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
To ensure a seamless mobility of users in the scenario with flying base stations (FlyBSs) and
static ground base stations (GBSs), an efficient handover mechanism is required. In this …
static ground base stations (GBSs), an efficient handover mechanism is required. In this …
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 …
5G handover using reinforcement learning
V Yajnanarayana, H Rydén… - 2020 IEEE 3rd 5G World …, 2020 - ieeexplore.ieee.org
In typical wireless cellular systems, the handover mechanism involves reassigning an
ongoing session handled by one cell into another. In order to support increased capacity …
ongoing session handled by one cell into another. In order to support increased capacity …
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 …
traditional macrocells, and thus a moving user equipment (UE) usually experiences a more …
[HTML][HTML] Autonomous handover parameter optimisation for 5G cellular networks using deep deterministic policy gradient
The ultra-dense network (UDN) is considered a vital technology for 5G mobile
communications due to its ability to transmit high data rates in high-traffic environments …
communications due to its ability to transmit high data rates in high-traffic environments …
A Handover Assistance Algorithm Based on SDN and Machine Learning
Z Yang, X Liu, M Wu, W Huang - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
In the 5th generation mobile network (5G), microcells are densely deployed for spatial
multiplexing, working in concert with traditional macrocells. 5G network uses not only the …
multiplexing, working in concert with traditional macrocells. 5G network uses not only the …
Handover control in wireless systems via asynchronous multiuser deep reinforcement learning
In this paper, we propose a two-layer framework to learn the optimal handover (HO)
controllers in possibly large-scale wireless systems supporting mobile Internet-of-Things …
controllers in possibly large-scale wireless systems supporting mobile Internet-of-Things …