5 papers
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…
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…
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…