While the 5G New Radio (NR) network promises a huge uplift of the uplink throughput, the
improvement can only be seen when the User Equipment (UE) is connected to the high …

In this work, an experiment to examine the feasibility of maximum downlink throughput
prediction in 5G networks through machine learning is conducted. The goal is to find a …

Mobile communication technology is evolving rapidly and becoming increasingly ubiquitous,
thereby increasing the demand for uplink data-intensive applications (eg, personal …

The emergence of novel cellular network technologies, within 5G, are envisioned as key
enablers of a new set of use-cases, including industrial automation, intelligent …

Abstract Vehicle-To-Everything (V2X) applications pose challenging Quality of Service
(QoS) needs on mobile networks. These demand high data rates and low latency. 5G, with …

Throughput prediction remains a relevant and challenging problem in the area of wireless
networking. Both users and service providers would benefit from the predictive Quality of …

Throughput Prediction is one of the primary preconditions for the uninterrupted operation of
several network-aware mobile applications, namely video streaming. Recent works have …

Recently, there have been many attempts to apply Machine Learning (ML)-based prediction
mechanisms In wireless networks. One open question is how reliable such predictions can …

In order to satisfy the ever-growing Quality of Service (QoS) requirements of innovative
services, cellular communication networks are constantly evolving. Recently, the 5G Non …

The rapid evolution of cellular technologies has resulted in a drastic increase in mobile data
traffic. Particularly, in 5G cellular networks, the design of accurate time-series models …