SWIFT
Overview
SWIFT focuses on the coexistence of active and passive wireless systems in the same frequency bands. While active wireless systems are critical for modern commerce, transportation, health, science, and defense, passive remote sensing services are also indispensable to their applications in agriculture, climate modeling and prediction, forecasting, and more. However, the growth of active wireless systems increases the interference experienced by passive systems, which can render them useless in extreme cases. Thus, this project aims to develop advanced signal processing, resource management, and artificial intelligence techniques for both active and passive users to ensure functional coexistence in shared frequency bands.
RESOURCES
SWIFT-related sites: Webpage
Meta-Learning for Wireless Interference Identification
Using MATLAB 5G Toolbox for SDR 5G NR Waveform Generation
COLLABORATORS
People
Faculty
Dr. Vuk Marojevic
Associate Professor
Mississippi State University
Dr. Mehmet Kurum
Associate Professor
Mississippi State University
Dr. Ali Cafer Gurbuz
Assistant Professor
Mississippi State University
Dr. Fatemeh Afghah
Associate Professor
Clemson University
Dr. Nicholas Mastronarde
Associate Professor
University of Buffalo
Students
Walaa Alqwider
PhD Candidate
Mississippi State University
Md Mehedi Farhad
PhD Candidate
Mississippi State University
Ahmed Manavi Alam
PhD Candidate
Mississippi State University
Mohammad Koosha
PhD Student
University at Buffalo
Ali Owfi
PhD Student
Clemson University
Anjali Omer
PhD Student
University at Buffalo
Michael Seguin
PhD Student
University at Buffalo
Mahshid Rezakhani
MS Student
Clemson University
PUBLICATIONS
Submitted or in preparation
W. Alqwider, A. S. Abdalla and V. Marojevic "5G Advanced: Wireless Channel Virtualization and Resource Mapping for Real Time Spectrum Sharing," submitted.
M. Koosha and N. Mastronarde, "On the RFI Induced on Space-borne Radiometers by Active Terrestrial Wireless Networks" in preparation.
M. Koosha and N. Mastronarde, "RFI minimization in the Soil Moisture Active Passive (SMAP) Satellite using Convex Optimization," in preparation.
M. Seguin, A. Omer, F. Malandra, and N. Mastronarde, "Deep Reinforcement Learning for Downlink Scheduling in 5G Networks: A Survey," in preparation.
A. Owfi, F. Afghah, J. Ashdown, "Meta-learning for Wireless Interference Identification", submitted.
Accepted
A. M. Alam, A. C. Gurbuz, and M. Kurum, "High-Resolution Radio Frequency Interference Detection In Microwave Radiometry Using Deep Learning," in IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, 2023.
M. M. Farhad, S. Biswas, A. M. Alam, A. C. Gurbuz, and M. Kurum, "SDR Based Agile Radiometer With Onboard RFI Processing On A Small UAS," in IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, 2023.
W. Alqwider, A. M. Alam, M. M. Farhad, M. Kurum, A. C. Gurbuz, and V. Marojevic, "Software Radio Testbed For 5G And L-Band Radiometer Coexistence Research," in IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, 2023.
M. Koosha and N. Mastronarde, "Minimizing Estimation Error Variance Using a Weighted Sum of Samples from the Soil Moisture Active Passive (SMAP) Satellite," RFI minimization in the Soil Moisture Active Passive (SMAP) Satellite using Convex Optimization," IEEE International Geosciences and Remote Sensing Symposium (IGARSS), Pasadena, California, Sept. 2023.
A. Omer, F. Malandra, J. Chakareski, and N. Mastronarde, "Performance Evaluation of 5G Delay-Sensitive Single-Carrier Multi-User Downlink Scheduling," IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Toronto, ON, Canada, Sept. 2023.
M. Seguin, A. Omer, F. Malandra, and N. Mastronarde, "Deep Reinforcement Learning for Downlink Scheduling in 5G Networks: A Survey," IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Toronto, ON, Canada, Sept. 2023.
A. M. Alam, M. Kurum and A. C. Gurbuz, "Radio Frequency Interference Detection for SMAP Radiometer Using Convolutional Neural Networks," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 15, pp. 10099-10112, 2022, doi: 10.1109/JSTARS.2022.3223198.
A. M. Alam, A. Gurbuz, and M. Kurum, "SMAP Radiometer RFI Prediction with Deep Learning Using Antenna Counts," IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Kuala Lumpur, Malaysia, July 2022.
W. AlQwider, A. Dahal and V. Marojevic, "Software Radio with MATLAB Toolbox for 5G NR Waveform Generation," 2022 18th International Conference on Distributed Computing in Sensor Systems (DCOSS), 2022, pp. 430-433. 10.1109/DCOSS54816.2022.00078
W. AlQwider, T. F. Rahman and V. Marojevic, "Deep Q-Network for 5G NR Downlink Scheduling," Proc. IEEE ICC'22 ,May 2022, pp. 312-317. 10.1109/ICCWorkshops53468.2022.9814547
H. Mohammadi, W. Al-Qwider, T.F. Rahman, and V. Marojevic, "AI-Driven Demodulators for Nonlinear Receivers in Shared Spectrum with High-Power Blockers," Proc. IEEE WCNC'22, Austin, TX, USA, April 2022, pp. 1-6. [Link]
N. Namvar, and F. Afghah, "Joint 3D Placement and Interference Management for Drone Small Cells”, IEEE Asilomar Conference on Signals, Systems, and Computers (ASILOMAR), Oct. 2021. [Link]
J. Hu, S. K. Moorthy, A. Harindranath, Z. Guan, N. Mastronarde, E. S. Bentley, and S. Pudlewski, “SwarmShare: Mobility-resilient Spectrum Sharing for Swarm UAV Networking in the 6 Ghz Band,” IEEE International Conference on Sensing, Communication, and Networking (SECON), July 2021. (Acceptance rate: 26.4%) [Link]
M. Gharib, S. Nandadapu, and F. Afghah, "An Exhaustive Study of Using Commercial LTE Network for UAV Communication in Rural Areas”, IEEE ICC Workshop on Integrating UAVs into 5G and Beyond, July 2021. [Link]
Shamsoshoara, F. Afghah, E. Blasch, J. Ashdown, and M. Bennis, "UAV-assisted Communication in Remote Disaster Areas using Imitation Learning”, IEEE Open Journal of the Communication Society, Special Issue on Aerial Wireless Networks: Drones for Communications and Communications for Drones, March 2021. [Link]
A. S. Abdalla and V. Marojevic, "Communications Standards for Unmanned Aircraft Systems: The 3GPP Perspective and Research Drivers," IEEE Communications Standards Magazine, Vol. 5, Iss. 1, pp. 70-77, March 2021. [Link]
M. M. Farhad , S. Biswas, M. A. S. Rafi, A. Gurbuz, and M. Kurum, "Design and Implementation of a Software Defined Radio-Based Radiometer Operating from a Small Unmanned Aircraft Systems," IEEE International Symposium on Antennas and Propagation, Denver, Colorado, July 2022.
A. Owfi, F. Afghah, J. Ashdown, "Meta-learning for Wireless Interference Identification", IEEE Wireless Communications and Networking Conference (WCNC) 2023
A. Owfi, F. Afghah, "Autoencoder-based Radio Frequency Interference Mitigation for SMAP Passive Radiometer ", IEEE International Geosciences and Remote Sensing Symposium (IGARSS) 2023.
A. Owfi, CC. Lin, L. Guo, F. Afghah, J. Ashdown, K. Turck, "A Meta-learning based Generalizable Indoor Localization Model using Channel State Information ", IEEE Global Communications (GLOBECOM) 2023