14 citations · 17 across the 17 of their papers we have counts for
18 papers
Optimizing Energy and Data Collection in UAV-aided IoT Networks using Attention-based Multi-Objective Reinforcement Learning
Babacar Toure, Dimitrios Tsilimantos, Omid Esrafilian +1
Due to their adaptability and mobility, Unmanned Aerial Vehicles (UAVs) are becoming increasingly essential for wireless network services, particularly for data harvesting tasks. I…
TDoA-Based Self-Supervised Channel Charting with NLoS Mitigation
Mohsen Ahadi, Omid Esrafilian, Florian Kaltenberger +1
Channel Charting (CC) has emerged as a promising framework for data-driven radio localization, yet existing approaches often struggle to scale globally and to handle the distortion…
Experimental Insights from OpenAirInterface 5G positioning Testbeds: Challenges and solutions
Mohsen Ahadi, Adeel Malik, Omid Esrafilian +2
5G New Radio (NR) is a key enabler of accurate positioning in smart cities and smart factories. This paper presents the experimental results from three 5G positioning testbeds runn…
First Results on UAV-aided User Localization Using ToA and OpenAirInterface in 5G NR
Omid Esrafilian, Rakesh Mundlamuri, Florian Kaltenberger +2
This paper considers the challenge of localizing ground users with the help of a radio-equipped unmanned aerial vehicle (UAV) that collects measurements from users. We utilize time…
Global Scale Self-Supervised Channel Charting with Sensor Fusion
Omid Esrafilian, Mohsen Ahadi, Florian Kaltenberger +1
The sensing and positioning capabilities foreseen in 6G have great potential for technology advancements in various domains, such as future smart cities and industrial use cases. C…
Communication-Efficient Federated Learning via Regularized Sparse Random Networks
Mohamad Mestoukirdi, Omid Esrafilian, David Gesbert +2
This work presents a new method for enhancing communication efficiency in stochastic Federated Learning that trains over-parameterized random networks. In this setting, a binary ma…