Artificial intelligence-powered mobile edge computing-based anomaly detection in cellular networks
Escalating cell outages and congestion—treated as anomalies—cost a substantial revenue
loss to the cellular operators and severely affect subscriber quality of experience. State-of …
loss to the cellular operators and severely affect subscriber quality of experience. State-of …
Deep learning-based big data-assisted anomaly detection in cellular networks
5G is envisioned to have an artificial intelligence (AI)-empowerment to efficiently plan,
manage and optimize the extremely complex network by leveraging colossal amount of data …
manage and optimize the extremely complex network by leveraging colossal amount of data …
Mobile edge computing-based data-driven deep learning framework for anomaly detection
5G is anticipated to embed an artificial intelligence (AI)-empowerment to adroitly plan,
optimize and manage the highly complex network by leveraging data generated at different …
optimize and manage the highly complex network by leveraging data generated at different …
Call detail records driven anomaly detection and traffic prediction in mobile cellular networks
Mobile networks possess information about the users as well as the network. Such
information is useful for making the network end-to-end visible and intelligent. Big data …
information is useful for making the network end-to-end visible and intelligent. Big data …
Semi-supervised learning based big data-driven anomaly detection in mobile wireless networks
With rising capacity demand in mobile networks, the infrastructure is also becoming
increasingly denser and complex. This results in collection of larger amount of raw data (big …
increasingly denser and complex. This results in collection of larger amount of raw data (big …
Deep learning based detection of sleeping cells in next generation cellular networks
The growing subscriber Quality of Experience demands are posing significant challenges to
the mobile cellular network operators. One such challenge is the autonomic detection of …
the mobile cellular network operators. One such challenge is the autonomic detection of …
STAD: Spatio-temporal anomaly detection mechanism for mobile network management
A Dridi, C Boucetta, SE Hammami… - … on Network and …, 2020 - ieeexplore.ieee.org
Unusual Spatio-Temporal fluctuations in cellular network traffic may lead to drastic network
management misbehaviors and at least abnormal drops in quality of experience. It is also …
management misbehaviors and at least abnormal drops in quality of experience. It is also …
Big data analytics for user-activity analysis and user-anomaly detection in mobile wireless network
The next generation wireless networks are expected to operate in fully automated fashion to
meet the burgeoning capacity demand and to serve users with superior quality of …
meet the burgeoning capacity demand and to serve users with superior quality of …
Anomaly detection in cellular network data using big data analytics
IA Karatepe, E Zeydan - European Wireless 2014; 20th …, 2014 - ieeexplore.ieee.org
Anomaly detection is a key component in which perturbations from a normal behavior
suggests a misconfigured/mismatched data in related systems. In this paper, we present a …
suggests a misconfigured/mismatched data in related systems. In this paper, we present a …
CellPAD: Detecting performance anomalies in cellular networks via regression analysis
How to accurately detect Key Performance Indicator (KPI) anomalies is a critical issue in
cellular network management. We present CellPAD, a unified performance anomaly …
cellular network management. We present CellPAD, a unified performance anomaly …