Deep learning in mobile and wireless networking: A survey
The rapid uptake of mobile devices and the rising popularity of mobile applications and
services pose unprecedented demands on mobile and wireless networking infrastructure …
services pose unprecedented demands on mobile and wireless networking infrastructure …
A survey on the handover management in 5G-NR cellular networks: aspects, approaches and challenges
With the purpose of providing higher data rate and ultra-reliable and low-latency
communications for the users, employing the small cells in the upcoming Fifth-Generation …
communications for the users, employing the small cells in the upcoming Fifth-Generation …
Machine learning meets communication networks: Current trends and future challenges
The growing network density and unprecedented increase in network traffic, caused by the
massively expanding number of connected devices and online services, require intelligent …
massively expanding number of connected devices and online services, require intelligent …
Deep learning at the mobile edge: Opportunities for 5G networks
M McClellan, C Cervelló-Pastor, S Sallent - Applied Sciences, 2020 - mdpi.com
Mobile edge computing (MEC) within 5G networks brings the power of cloud computing,
storage, and analysis closer to the end user. The increased speeds and reduced delay …
storage, and analysis closer to the end user. The increased speeds and reduced delay …
Mobility prediction: A survey on state-of-the-art schemes and future applications
H Zhang, L Dai - IEEE access, 2018 - ieeexplore.ieee.org
Recently, mobility has gathered tremendous interest as the users' desire for consecutive
connections and better quality of service has increased. An accurate prediction of user …
connections and better quality of service has increased. An accurate prediction of user …
Mobility management in emerging ultra-dense cellular networks: A survey, outlook, and future research directions
The exponential rise in mobile traffic originating from mobile devices highlights the need for
making mobility management in future networks even more efficient and seamless than ever …
making mobility management in future networks even more efficient and seamless than ever …
AutoMEC: LSTM-based user mobility prediction for service management in distributed MEC resources
The 5th generation of the cellular mobile communication system (5G) is in the meantime
stepwise being deployed in mobile carriers' infrastructure. Various standardization tracks as …
stepwise being deployed in mobile carriers' infrastructure. Various standardization tracks as …
Reinforcement learning-based vehicle-cell association algorithm for highly mobile millimeter wave communication
Vehicle-to-everything (V2X) communication is a growing area of communication with a
variety of use cases. This paper investigates the problem of vehicle-cell association in …
variety of use cases. This paper investigates the problem of vehicle-cell association in …
An adaptive cell selection scheme for 5G heterogeneous ultra-dense networks
IA Alablani, MA Arafah - IEEE Access, 2021 - ieeexplore.ieee.org
Fifth-generation (5G) cellular networks are a promising technology to meet the rapid growth
in wireless traffic. Small cells are critical in fulfilling the requirements of 5G networks. A …
in wireless traffic. Small cells are critical in fulfilling the requirements of 5G networks. A …
Using machine learning for handover optimization in vehicular fog computing
S Memon, M Maheswaran - Proceedings of the 34th ACM/SIGAPP …, 2019 - dl.acm.org
Smart mobility management would be an important prerequisite for future fog computing
systems. In this research, we propose a learning-based handover optimization for the …
systems. In this research, we propose a learning-based handover optimization for the …