Tri Nhu Do

Assistant Professor

Polytechnique Montréal

Canada

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About

Tri Nhu Do is an Assistant Professor at Polytechnique Montréal, Canada. His research primarily focuses on communication networks, including statistical characterization and performance optimization for various scenarios such as ultra-dense LEO networks and RIS-assisted systems. Recent articles highlight his work on topics like federated learning for jamming detection, deep learning for interference classification, and joint computation offloading in UAV networks.

Articles (16)

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2025

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2025

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2024

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2024

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2023

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2023

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2023

Collaborators (2)

KYUSUNG SHIM

Assistant Professor

Hankyong National University

SOUTH KOREA

View details

Beongku An

Professor

Hongik University

SOUTH KOREA

View details

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Tri Nhu Do

Research Interests

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About

Articles (16)

Transfer Learning-Empowered Physical Layer Security in Aerial Reconfigurable Intelligent Surfaces-Based Mobile Networks

Unsupervised Learning-Based Joint Beamforming and Phase-Shift Optimization for RIS-Assisted DeepMIMO With Large-Scale Arrays

Ground-to-AAV and RIS-Assisted AAV-to-Ground Communication Under Channel Aging: Statistical Characterization and Outage Performance

Fast Beam Placement for Ultra-Dense LEO Networks

DRL-Based Maximization of the Sum Cross-Layer Achievable Rate for Networks Under Jamming

Deep Transfer Learning-Based Performance Prediction of URLLC in Independent and Not Necessarily Identically Distributed Interference Networks

Federated Learning-Enabled Jamming Detection for Stochastic Terrestrial and Non-Terrestrial Networks

Joint Computation Offloading and Target Tracking in Integrated Sensing and Communication Enabled UAV Networks

Joint Devices and IRSs Association for Terahertz Communications in Industrial IoT Networks

Joint Power and User Allocation in Coexistence of eMBB and URLLC Services

Joint Task Offloading and Radio Resource Management in Stochastic MEC Systems

Multi-IRS-Aided Terahertz Networks: Channel Modeling and User Association With Imperfect CSI

Deep Learning-Based Interference Detection, Classification, and Forecasting Algorithm for ESM Radar Systems

Adaptive Decoding Mechanisms for UAV-Enabled Double-Uplink Coordinated NOMA

Deep Learning-Enabled Deceptive Jammer Detection for Low Probability of Intercept Communications

Channel Characterization of UAV-RIS-Aided Systems With Adaptive Phase-Shift Configuration

Collaborators (2)

KYUSUNG SHIM

Beongku An

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