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Event-Driven Source Traffic Prediction in Machine-Type Communications Using LSTM Networks
Source traffic prediction is one of the main challenges of enabling pred...
01/12/2021 ∙ by Thulitha Senevirathna, et al. ∙
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Contextual Bandit Learning for Machine Type Communications in the Null Space of Multi-Antenna Systems
In this paper, a novel approach based on the concept of opportunistic sp...
05/23/2019 ∙ by Samad Ali, et al. ∙
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Cyber-Physical Security and Safety of Autonomous Connected Vehicles: Optimal Control Meets Multi-Armed Bandit Learning
Autonomous connected vehicles (ACVs) rely on intra-vehicle sensors such ...
12/13/2018 ∙ by Aidin Ferdowsi, et al. ∙
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Sleeping Multi-Armed Bandit Learning for Fast Uplink Grant Allocation in Machine Type Communications
Scheduling fast uplink grant transmissions for machine type communicatio...
10/30/2018 ∙ by Samad Ali, et al. ∙
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A Directed Information Learning Framework for Event-Driven M2M Traffic Prediction
Burst of transmissions stemming from event-driven traffic in machine typ...
08/27/2018 ∙ by Samad Ali, et al. ∙
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Fast Uplink Grant for Machine Type Communications: Challenges and Opportunities
The notion of a fast uplink grant is emerging as a promising solution fo...
01/15/2018 ∙ by Samad Ali, et al. ∙
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Samad Ali
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University of Oulu
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Virginia Polytechnic Institute and State University
