activity
20192023
most citedOn-board Change Detection for Resource-efficient Earth Observation with LEO Satellites

1 citations · 1 across the 7 of their papers we have counts for

collaborators

7 papers

eess.SP2023★ 1 cited

On-board Change Detection for Resource-efficient Earth Observation with LEO Satellites

Van-Phuc Bui, Thinh Q. Dinh, Israel Leyva-Mayorga +3

The amount of data generated by Earth observation satellites can be enormous, which poses a great challenge to the satellite-to-ground connections with limited rate. This paper con…

cs.IT2022

Efficient Hamiltonian Reduction for Quantum Annealing on SatCom Beam Placement Problem

Thinh Q. Dinh, Son Hoang Dau, Eva Lagunas +1

Beam Placement (BP) is a well-known problem in Low-Earth Orbit (LEO) satellite communication (SatCom) systems, which can be modelled as an NP-hard clique cover problem. Recently, q…

cs.IT2021

Enabling Large-Scale Federated Learning over Wireless Edge Networks

Thinh Quang Dinh, Diep N. Nguyen, Dinh Thai Hoang +2

Major bottlenecks of large-scale Federated Learning(FL) networks are the high costs for communication and computation. This is due to the fact that most of current FL frameworks on…

cs.IT2021

Low-Latency and Secure Computation Offloading Assisted by Hybrid Relay-Reflecting Intelligent Surface

Khac-Hoang Ngo, Nhan Thanh Nguyen, Thinh Quang Dinh +2

Recently, the hybrid relay-reflecting intelligent surface (HRRIS) has been introduced as a spectral- and energy-efficient architecture to assist wireless communication systems. In…

cs.IT2021

In-network Computation for Large-scale Federated Learning over Wireless Edge Networks

Thinh Quang Dinh, Diep N. Nguyen, Dinh Thai Hoang +2

Most conventional Federated Learning (FL) models are using a star network topology where all users aggregate their local models at a single server (e.g., a cloud server). That caus…

cs.IT2020

Online Resource Procurement and Allocation in a Hybrid Edge-Cloud Computing System

Thinh Quang Dinh, Ben Liang, Tony Q. S. Quek +1

By acquiring cloud-like capacities at the edge of a network, edge computing is expected to significantly improve user experience. In this paper, we formulate a hybrid edge-cloud co…

eess.SP2019

Joint Optimization of Execution Latency and Energy Consumption for Mobile Edge Computing with Data Compression and Task Allocation

Minh Hoang Ly, Thinh Quang Dinh, Ha Hoang Kha

In this paper, we consider the mobile edge offloading scenario consisting of one mobile device (MD) with multiple independent tasks and various remote edge devices. In order to sav…