Výsledky vyhľadávania - "Mobile Networks"

Sample Selection Methods for Federated Continual Learning in a Time Series Context

Autori: Ickin, Selim Lan, Xiaoyu Angelova, Milena a ďalší

Zdroj: IEEE Access. 13:189057-189073

Predmety: AI-native networks, AI/ML model lifecycle management, catastrophic forgetting, concept drift, Federated continual learning, future mobile networks, sample selection, time series data, Complex networks, Data aggregation, Data reduction, Federated learning, Information management, Learning systems, Life cycle, Mobile telecommunication systems, Reconfigurable hardware, Sampling, Spatio-temporal data, Time series, Time varying networks, AI-native network, AI/machine learning model lifecycle management, Concept drifts, Continual learning, Future mobile network, Lifecycle management, Machine learning models, Samples selection, Time-series data, Behavioral research, Digital storage

Popis súboru: electronic

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:bth-28916
https://doi.org/10.1109/ACCESS.2025.3628353

MOSE: A Novel Orchestration Framework for Stateful Microservice Migration at the Edge

Autori: Calagna, Antonio Yu, Yenchia Giaccone, Paolo a ďalší

Zdroj: IEEE Transactions on Network and Service Management. 22(5):4827-4841

Predmety: computer vision, machine learning, service migration, mobile networks, Edge computing

Popis súboru: electronic

Prístupová URL adresa: https://research.chalmers.se/publication/548731
https://research.chalmers.se/publication/548731/file/548731_Fulltext.pdf

Self-Supervised Pretraining for User Performance Prediction Under Scarce Data Conditions

Autori: Rao, Akhila Boman, Magnus

Zdroj: IEEE Transactions on Network and Service Management.

Predmety: generalizability, machine learning, mobile networks, sample efficiency, self-supervised learning, structured data, tabular data, telecom networks, user performance prediction

Popis súboru: print

Prístupová URL adresa: https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-372578
https://doi.org/10.1109/TNSM.2025.3622892

CABAD: A video dataset for benchmarking child aggression recognition

Autori: Shehzad Ali Md Tanvir Islam Ik Hyun Lee a ďalší

Zdroj: Alexandria Engineering Journal, Vol 127, Iss, Pp 1143-1157 (2025)

Predmety: Mobile networks for aggression detection, Child activity recognition, Real-time monitoring, TA1-2040, Engineering (General). Civil engineering (General), MobileViT, Attention LSTM, Child-aggressive activities

Prístupová URL adresa: https://doaj.org/article/49331e70a8cd4308bbca2c041fe58a46

Application of network calculus to analyze eCPRI traffic delays in 4G/5G fronthaul mobile networks

Autori: A. V. Roslyakov V. V. Gerasimov

Zdroj: Учёные записки Казанского университета: Серия Физико-математические науки, Vol 167, Iss 2, Pp 351-366 (2025)

Predmety: network calculus, 4g/5g mobile networks, arrival curve, delay analysis, QA1-939, service curve, ecpri, fronthaul segment, Mathematics

Prístupová URL adresa: https://doaj.org/article/aa2f440e62674605881ac751820ebe6d

Data-driven Energy Optimization in Mobile Networks with User Experience Guarantees

Autori: Dang, Anh-Khoa Khalifé, Hicham Sintorn, Mathias a ďalší

Prispievatelia: Dang, Anh-Khoa Khalifé, Hicham Sintorn, Mathias a ďalší

Zdroj: IEEE INFOCOM 2025 - IEEE Conference on Computer Communications. :1-10

Predmety: [INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], Deep Reinforcement Learning, [INFO.INFO-MC] Computer Science [cs]/Mobile Computing, Energy saving, Carrier Shutdown, [INFO] Computer Science [cs], Mobile Networks, 5G, network analytics

Popis súboru: application/pdf

Prístupová URL adresa: https://hal.science/hal-05040259v1
https://doi.org/10.1109/infocom55648.2025.11044545
https://hal.science/hal-05040259v1/document

Procedimento de Acesso Aleatório em Redes 5G/6G Integradas com Satélites de Órbita Terrestre Baixa

Autori: Mosca, Eduardo Andrade, Tiago Barbosa Pereira, Rafael a ďalší

Zdroj: Anais do V Workshop de Redes 6G (W6G 2025). :33-40

Predmety: mobile networks, NTN, 5G, 6G

Cost-Effective Measurement Setup for Analyzing Signal Coverage in 4G/5G Mobile Networks

Autori: Polák, Ladislav Baránek, Michal Kufa, Jan a ďalší

Zdroj: 2025 35th International Conference Radioelektronika (RADIOELEKTRONIKA). :1-6

Predmety: coverage mapping, key performance indicators (KPIs), 4G and 5G mobile networks, data analysis, interpolation

Popis súboru: text; application/pdf

Prístupová URL adresa: http://hdl.handle.net/11012/255542

Prediction-Based Discontinuous Reception Mechanism for Extended Reality Applications

Autori: Yahya, Sekinat Stanica, Razvan

Prispievatelia: Yahya, Sekinat Stanica, Razvan

Zdroj: 2025 IEEE 22nd Consumer Communications & Networking Conference (CCNC). :1-6

Predmety: Energy Optimisation, [INFO.INFO-NI] Computer Science [cs]/Networking and Internet Architecture [cs.NI], Extended Reality, Mobile Networks Extended Reality Radio Resource Control Energy Optimisation, Mobile Networks, Radio Resource Control

Popis súboru: application/pdf

Prístupová URL adresa: https://hal.science/hal-04945405v1

RESEARCH ON BEAMFORMING TECHNIQUES IN 5G NETWORK

Autori: HOANG Van Thuc DOAN Manh Cuong

Zdroj: Tạp chí Khoa học, Vol 54, Iss 2A, Pp 5-12 (2025)

Predmety: Social sciences (General), H1-99, Technology, 5g mobile networks, antenna arrays for 5g, antenna beamforming, beamforming

Prístupová URL adresa: https://doaj.org/article/fe568708dd5d455d8f4fd4cee65c6be6

Impact of multipath on anchor selection strategies for UAV localization in mobile networks

Autori: Luca Reggiani Alberto Facheris

Zdroj: Proceedings of the Estonian Academy of Sciences, Vol 74, Iss 2S, Pp 322-331 (2025)

Predmety: mobile networks, Science, uavs, localization, 5g

DeExp: Revealing Model Vulnerabilities for Spatio-Temporal Mobile Traffic Forecasting With Explainable AI

Autori: Serly Moghadas Gholian Claudio Fiandrino Narseo Vallina-Rodríguez a ďalší

Zdroj: IEEE Transactions on Mobile Computing. 24:5245-5263

Predmety: mobile networks, deep learning, explainable ai

Prístupová URL adresa: https://hdl.handle.net/20.500.12761/1889

Joint Communication and Sensing in OTFS-Based UAV Networks

Autori: Alessandro Nordio Carla Fabiana Chiasserini Emanuele Viterbo

Zdroj: IEEE Transactions on Vehicular Technology. 74:9445-9460

Predmety: Signal Processing (eess.SP), FOS: Computer and information sciences, UAVs, OTFS, Mobile networks, Position, Velocity, Localization, Computer Science - Information Theory, Information Theory (cs.IT), FOS: Electrical engineering, electronic engineering, information engineering, Electrical Engineering and Systems Science - Signal Processing

Popis súboru: application/pdf

Prístupová URL adresa: http://arxiv.org/abs/2311.17742
https://ieeexplore.ieee.org/document/10891196
https://doi.org/10.1109/TVT.2025.3542489
https://hdl.handle.net/11583/2997485

Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting

Autori: Nikolaos Pavlidis Vasileios Perifanis Selim F. Yilmaz a ďalší

Prispievatelia: Nikolaos Pavlidis Vasileios Perifanis Selim F. Yilmaz a ďalší

Zdroj: IEEE Transactions on Sustainable Computing

Predmety: Optimization, FOS: Computer and information sciences, Computer Science - Machine Learning, federated learning, mobile networks, Computer Science - Artificial Intelligence, Data models, Time series analysis, Servers, Computational modeling, [INFO] Computer Science [cs], Collaboration, Machine Learning (cs.LG), Predictive models, machine learning, Artificial Intelligence (cs.AI), Training, [INFO]Computer Science [cs], time series forecasting, traffic prediction, 5G, Accuracy, 6G, Forecasting

Prístupová URL adresa: http://arxiv.org/abs/2412.04081

Application of Experimental Method for the Delay Estimation in Cellular Mobile Networks

Autori: Brodnevs Deniss Kutins Aleksandrs

Zdroj: Transport and Telecommunication, Vol 26, Iss 2, Pp 160-174 (2025)

Predmety: delays, mobile communication, experimental method, cellular mobile networks, remotely guided vehicles, remotely piloted aircraft, K4011-4343, Transportation and communication

Prístupová URL adresa: https://doaj.org/article/987fe7689b374ea8a8ca719e4d3941ad

OTFS vs. OFDM in High-speed Vehicular Traffic Scenarios

Autori: Alessandro Compagnoni Roberto Garello Riccardo Tuninato a ďalší

Zdroj: 2025 IEEE Wireless Communications and Networking Conference (WCNC). :1-6

Predmety: OFDM, OTFS, Mobile networks, vehicular networks, V2X communications

Popis súboru: application/pdf

Prístupová URL adresa: https://hdl.handle.net/11583/2995832

Energy-Efficient Task Offloading Using Reinforcement Learning for Dependent Tasks in Cloud-Edge-Device Systems

Autori: Afrasiabi, Seyedeh Naboulsi, Diala Stanica, Razvan

Prispievatelia: Afrasiabi, Seyedeh Naboulsi, Diala Stanica, Razvan

Zdroj: 2025 28th Conference on Innovation in Clouds, Internet and Networks (ICIN). :9-16

Predmety: Task offloading, Energy-efficiency, [INFO.INFO-NI] Computer Science [cs]/Networking and Internet Architecture [cs.NI], Dependent Task, RL, MEC, Mobile Networks

Popis súboru: application/pdf

Prístupová URL adresa: https://inria.hal.science/hal-04881133v1

A Survey on Direct-to-Device Satellite Communications: Advances, Challenges, and Prospects

Autori: Pasandi, Hannaneh Fraire, Juan Ratnasamy, Sylvia a ďalší

Prispievatelia: Pasandi, Hannaneh Fraire, Juan Ratnasamy, Sylvia a ďalší

Zdroj: Proceedings of the 2nd International Workshop on LEO Networking and Communication. :7-12

Predmety: [SCCO.COMP] Cognitive science/Computer science, direct-to-cell, Networks → Mobile networks, CCS CONCEPTS Networks → Mobile networks direct-to-cell direct-to-smartphone, direct-to-smartphone, CCS CONCEPTS

Popis súboru: application/pdf

Machine Learning-Based Anomaly Detection and Root Cause Analysis in Mobile Networks

Autori: Nikula, Miro Markus Correia, Luis M. Grilo, António a ďalší

Prispievatelia: Nikula, Miro Markus Correia, Luis M. Grilo, António a ďalší

Zdroj: 2025 IEEE Wireless Communications and Networking Conference (WCNC). :01-06

Predmety: Machine Learning, Anomaly Detection, Root Cause Analysis, LSTM AE, Mobile Networks, DBSCAN

Popis súboru: application/pdf

Prístupová URL adresa: https://aaltodoc.aalto.fi/handle/123456789/136835

Quantifying NB-IoT Performance in 5G Use-Cases With Mixture of Regular and Stochastic Traffic

Autori: Pavel Masek Dmitri Moltchanov Martin Stusek a ďalší

Prispievatelia: Pavel Masek Dmitri Moltchanov Martin Stusek a ďalší

Zdroj: IEEE Internet of Things Journal. 12:7332-7347

Predmety: 5G Mobile Networks, mMTC, Narrowband IoT, Delay Performance, Mixture of Traffic Types

Popis súboru: text; application/pdf; fulltext

Prístupová URL adresa: http://hdl.handle.net/11012/252160