0000000000329452

AUTHOR

Aasmund Soraa

showing 1 related works from this author

Preamble Transmission Prediction for mMTC Bursty Traffic : A Machine Learning based Approach

2020

The evolution of Internet of things (IoT) towards massive IoT in recent years has stimulated a surge of traffic volume among which a huge amount of traffic is generated in the form of massive machine type communications. Consequently, existing network infrastructure is facing challenges when handling rapidly growing traffic load, especially under bursty traffic conditions which may more often lead to congestion. By proactively predicting the occurrence of congestion, we can implement necessary means and conceivably avoid congestion. In this paper, we propose a machine learning (ML) based model for predicting successful preamble transmissions at a base station and subsequently forecasting th…

Artificial neural networkComputer sciencebusiness.industryComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS05 social sciences050801 communication & media studies020206 networking & telecommunicationsComputingMilieux_LEGALASPECTSOFCOMPUTING02 engineering and technologyMachine learningcomputer.software_genrePreambleBase station0508 media and communicationsRecurrent neural networkTransmission (telecommunications)Traffic volume0202 electrical engineering electronic engineering information engineeringArtificial intelligencebusinesscomputerVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550
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