arXiv:2607. 18522v1 Announce Type: new Abstract: Mobile network operators monitor aggregated traffic volumes to assess the operational health of core network infrastructure.
By J. du Toit, G. Fita, J. Salzwedel, A. Stoltz, R. Wolhuter
This survey reviews deep learning methods for detecting anomalies in railway systems, organizing them by taxonomy of anomaly location, data representation, sensing modality, and temporal traits. It categorizes approaches—convolutional, recurrent, attention-based, autoencoders, GANs, transformers—into classification, prediction, reconstruction, and hybrid paradigms, and discusses data challenges, evaluation, metrics, and deployment issues such as edge‑cloud architectures and hardware constraints. The paper also offers a decision‑oriented framework linking anomaly characteristics, data properties, and operational constraints to guide the selection and deployment of suitable detection solutions.
By Ammar Bouketta, Smail Niar, Hamza Ouarnoughi
arXiv:2606. 05070v1 Announce Type: new Abstract: Train delay prediction is an important problem for both passengers and railway operators, yet progress in the field remains difficult to assess due to the lack of standardized datasets, prediction targets, and evaluation protocols.
By Cl\'ement Elliker, Mathis Le Bail, Cl\'ement Mantoux, Jesse Read, Sonia Vanier
The article discusses the growing role of AI and ML in 5G Radio Access Networks (RAN) and the need for a standardized life‑cycle management (LCM) framework to address issues like model drift, vendor lock‑in, and limited transparency. It reviews the five‑block LCM architecture introduced by 3GPP Releases 17–20, KPI‑driven monitoring mechanisms, and inter‑vendor collaboration schemes, and proposes an enhanced LCM framework that integrates reference‑model and vendor‑model development for two‑sided operation. The paper also identifies open challenges in resource‑efficient monitoring, environment drift detection, intelligent decision‑making, and flexible model training, laying groundwork for AI‑native transceivers in 6G.
By Chu-Hsiang Huang, Yuan-Chih Fan Chiang, Chao-Kai Wen, Geoffrey Ye Li
Reliable access selection in dynamic and heterogeneous indoor-outdoor environments is challenging because instantaneous radio measurements alone cannot capture future QoS degradation caused by mobilit...
arXiv:2608. 04710v1 Announce Type: cross Abstract: Integrated Sensing and Communication (ISAC) combines sensing and communication to efficiently utilize wireless resources and is emerging as a key paradigm for next-generation wireless networks.
By Ajeet Kumar Yadav, Sankaran Balasubramaniam, Aritra Chatterjee, Vinod Aduru, Yogesh Simmhan, Pandarasamy Arjunan