LinkForecast: Cellular link bandwidth prediction in LTE networks
Accurate cellular link bandwidth prediction can benefit upper-layer protocols significantly. In
this paper, we investigate how to predict cellular link bandwidth in LTE networks. We first …
this paper, we investigate how to predict cellular link bandwidth in LTE networks. We first …
Throughput prediction using machine learning in LTE and 5G networks
D Minovski, N Ögren, K Mitra… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
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 …
enablers of a new set of use-cases, including industrial automation, intelligent …
Realtime mobile bandwidth prediction using LSTM neural network and Bayesian fusion
With the increasing popularity of mobile Internet and the higher bandwidth requirement of
mobile applications, user Quality of Experience (QoE) is particularly important. For …
mobile applications, user Quality of Experience (QoE) is particularly important. For …
Realtime mobile bandwidth prediction using lstm neural network
With the popularity of mobile access Internet and the higher bandwidth demand of mobile
applications, user Quality of Experience (QoE) is particularly important. For bandwidth and …
applications, user Quality of Experience (QoE) is particularly important. For bandwidth and …
Comparison of machine learning techniques applied to traffic prediction of real wireless network
D Alekseeva, N Stepanov, A Veprev… - IEEE …, 2021 - ieeexplore.ieee.org
Today, the traffic amount is growing inexorably due to the increase in the number of devices
on the network. Researchers analyze traffic by identifying sophisticated dependencies …
on the network. Researchers analyze traffic by identifying sophisticated dependencies …
An empirical study of bandwidth predictability in mobile computing
J Yao, SS Kanhere, M Hassan - … of the third ACM international workshop …, 2008 - dl.acm.org
While bandwidth predictability has been well studied in static environments, it remains
largely unexplored in the context of mobile computing. To gain a deeper understanding of …
largely unexplored in the context of mobile computing. To gain a deeper understanding of …
On leveraging machine and deep learning for throughput prediction in cellular networks: Design, performance, and challenges
The highly dynamic wireless communication environment poses a challenge for many
applications (eg, adaptive multimedia streaming services). Providing accurate TP can …
applications (eg, adaptive multimedia streaming services). Providing accurate TP can …
4G LTE network throughput modelling and prediction
H Elsherbiny, HM Abbas, H Abou-zeid… - … 2020-2020 IEEE …, 2020 - ieeexplore.ieee.org
The past decade has witnessed a staggering evolution in cellular networks. Mobile wireless
technologies have undergone four distinct generations; from uncomplicated voice calls in …
technologies have undergone four distinct generations; from uncomplicated voice calls in …
Cellular traffic load prediction with LSTM and Gaussian process regression
Accurate cellular traffic load prediction is a pre-requisite for efficient and automatic network
planning and management. Considering diverse users' activities at different locations and …
planning and management. Considering diverse users' activities at different locations and …
The learning and prediction of application-level traffic data in cellular networks
Traffic learning and prediction is at the heart of the evaluation of the performance of
telecommunications networks and attracts a lot of attention in wired broadband networks …
telecommunications networks and attracts a lot of attention in wired broadband networks …