7 papers
UAV-Based 3D Spectrum Sensing: Insights on Altitude, Bandwidth, Trajectory, and Effective Antenna Patterns on REM Reconstruction
Mushfiqur Rahman, Sung Joon Maeng, Ismail Guvenc +4
Spectrum sensing and the generation of 3D Radio Environment Maps (REMs) are essential for enabling spectrum sharing within cognitive radio networks. While Uncrewed Aerial Vehicles…
GS-SBL: Bridging Greedy Pursuit and Sparse Bayesian Learning for Efficient 3D Wireless Channel Modeling
Mushfiqur Rahman, Ismail Guvenc, David Matolak
Robust cognitive radio development requires accurate 3D path loss models. Traditional empirical models often lack environment-awareness, while deep learning approaches are frequent…
Elevation- and Tilt-Aware Shadow Fading Correlation Modeling for UAV Communications
Mushfiqur Rahman, Ismail Guvenc, Mihail Sichitiu +4
Future wireless networks demand a more accurate understanding of channel behavior to enable efficient communication with reduced interference. Uncrewed Aerial Vehicles (UAVs) are p…
Curated Wireless Datasets for Aerial Network Research
Amir Hossein Fahim Raouf, Donggu Lee, Mushfiqur Rahman +18
This Review consolidates publicly available aerial wireless measurement datasets collected using AERPAW. We organize signal-level, power-level, and KPI-level datasets under a unifi…
3D Spectrum Awareness for Radio Dynamic Zones Using Kriging and Matrix Completion
Mushfiqur Rahman, Sung Joon Maeng, Ismail Guvenc +1
Radio Dynamic Zones (RDZs) are geographically defined areas specifically allocated for testing new wireless technologies. It is essential to safeguard the regular spectrum users ou…
Platform-Aware Channel Knowledge Mapping via Mutual Antenna Pattern Learning in 3D Wireless Links
Mushfiqur Rahman, Ismail Guvenc, Jason A. Abrahamson +1
This letter proposes a platform-aware framework to characterize wireless links by empirically modeling the `near-platform' scattering and reflections induced by the hardware mounti…