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3 August 2021

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

The current random access (RA) allocation techniques suffer from congestion and high signaling overhead while serving massive machine type communication (mMTC) applications. […]

25 January 2021

Event-Driven Source Traffic Prediction in Machine-Type Communications Using LSTM Networks

Source traffic prediction is one of the main challenges of enabling predictive resource allocation in machine-type communications (MTC). In this paper, a […]

21 April 2020

Sleeping Multi-Armed Bandit Learning for Fast Uplink Grant Allocation in Machine Type Communications

Scheduling fast uplink grant transmissions for machine type communications (MTCs) is one of the main challenges of future wireless systems. In this […]

25 November 2019

Contextual Bandit Learning for Machine Type Communications in the Null Space of Multi-Antenna Systems

Ensuring an effective coexistence of conventional broadband cellular users with machine type communications (MTCs) is challenging due to the interference from MTCs […]

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