Hirley Alves

Assist. Prof

Oulun Yliopisto

Finland

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Hirley Alves is an Assistant Professor at Oulun Yliopisto, Finland. His research interests include energy efficiency in wireless networks, specifically in areas such as low-energy adaptive clustering protocols, multi-UAV path optimization, and the integration of machine-type communication with satellite systems. He has contributed to the fields of IoT and communication technologies through various recent publications focusing on statistical QoS provisioning and energy-efficient signaling.

Articles (13)

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2024

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2024

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2023

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2023

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2022

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2022

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2022

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2022

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2022

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2022

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2022

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2022

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2022

Collaborators (4)

Eslam Eldeeb

University of Oulu

FINLAND

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Matti Latva-aho

University of Oulu

FINLAND

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Konstantin Mikhaylov

Assistant Professor (Tenure Track) of Convergent Wireless for IoT

University of Oulu

FINLAND

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Markku Juntti

Professor

Oulun Yliopisto

FINLAND

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Hirley Alves

Research Interests

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Articles (13)

Effective Energy Efficiency under Delay–Outage Probability Constraints and <inline-formula><math display="inline"><semantics><mrow><mi mathvariant="script">F</mi></mrow></semantics></math></inline-formula>-Composite Fading

Improvement of the Low-Energy Adaptive Clustering Hierarchy Protocol in Wireless Sensor Networks Using Mean Field Games

Joint Coherent and Non-Coherent Detection and Decoding Techniques for Heterogeneous Networks

Multi-UAV Path Learning for Age and Power Optimization in IoT With UAV Battery Recharge

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

Analysis and Simulation of LoRaWAN LR-FHSS for Direct-to-Satellite Scenario

CSI-Free Rotary Antenna Beamforming for Massive RF Wireless Energy Transfer

D2D Assisted Q-Learning Random Access for NOMA-Based MTC Networks

Effective Energy Efficiency and Statistical QoS Provisioning Under Markovian Arrivals and Finite Blocklength Regime

Enabling mMTC in Remote Areas: LoRaWAN and LEO Satellite Integration for Offshore Wind Farm Monitoring

Energy-Efficient Wake-Up Signalling for Machine-Type Devices Based on Traffic-Aware Long Short-Term Memory Prediction

Fog-RAN Enabled Multi-Connectivity and Multi-Cell Scheduling Framework for Ultra-Reliable Low Latency Communication

Minimization of the Worst Case Average Energy Consumption in UAV-Assisted IoT Networks

Collaborators (4)

Eslam Eldeeb

Matti Latva-aho

Konstantin Mikhaylov

Markku Juntti

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