Performance Analysis of ML-Based MTC Traffic Pattern Predictors-Reference-Cited by-同舟云学术

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Performance Analysis of ML-Based MTC Traffic Pattern Predictors

Published:2023-07 Issue:7 Volume:12 Page:1144-1148
ISSN:2162-2337
Container-title:IEEE Wireless Communications Letters
language:
Short-container-title:IEEE Wireless Commun. Lett.

Author:

Ruíz-Guirola David E.¹^ORCID,López Onel L. A.¹^ORCID,Montejo-Sánchez Samuel²^ORCID,Souza Richard Demo³^ORCID,Bennis Mehdi¹^ORCID

Affiliation:

1. Centre for Wireless Communications, University of Oulu, Oulu, Finland

2. Programa Institucional de Fomento a la Investigación, Desarrollo e Innovación, Universidad Tecnológica Metropolitana, Santiago, Chile

3. Department of Electrical Engineering, Federal University of Santa Catarina, Florianópolis, Brazil

Funder

Tekniikan Edis?miss??ti?n

ANID FONDECYT Iniciaci?n

Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico

6Genesis Flagship

RNP/MCTIC

FONDEQUIP-EQM

Print CAPES-UFSC ?Automation 4.0?

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/5962382/10177762/10091535.pdf?arnumber=10091535

Reference26 articles.

1. Traffic Prediction for Reconfigurable Access Scheme in Correlated Traffic MTC Networks

2. A Learning-Based Fast Uplink Grant for Massive IoT via Support Vector Machines and Long Short-Term Memory

3. A traffic model for machine-type communications using spatial point processes

4. Towards Energy Efficient 5G Networks Using Machine Learning: Taxonomy, Research Challenges, and Future Research Directions

5. Intelligent Traffic Adaptive Resource Allocation for Edge Computing-Based 5G Networks

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