In our rapidly expanding realm of advanced satellite and communication systems, passive radiometer sensors utilized in Earth observation, such as those for 5G, face an escalating challenge posed by radio frequency interference (RFI) stemming from human-generated signals. Effective methodologies to assess the impact of 5G on Earth observation radiometers are urgently needed. Unfortunately, the scarcity of substantial datasets in the radio frequency (RF) domain, particularly concerning active/passive coexistence, impedes progress. Our research presents a controlled test environment comprising a calibrated L-band radiometer and a 5G wireless communication system. Housed within a controlled chamber, this unique setup enables the observation and quantification of transmission effects across various frequency bands. Through the creation of a comprehensive dataset, our objective is to standardize and benchmark both wireless communication and passive sensing. Leveraging the capacity to analyze raw measurements, our test environment facilitates the detection and mitigation of RFI, promoting the harmonious coexistence of wireless communication and passive sensing technologies while establishing vital standards.
Dataset Download Link (V1): https://mstate-my.sharepoint.com/:f:/g/personal/aa2863_msstate_edu/Esvo2OU23pBDq1UmFqgFqJ8BHmAMKpDkuCrCwgNHwBEX_Q?e=2dNgtM
- A. M. Alam, M. M. Farhad, W. Al-Qwider, A. Owfi, M. Koosha, N. Mastronarde, F. Afghah, V. Marojevic, M. Kurum, and A. C. Gurbuz, "A Physical Testbed and Open Dataset for Benchmarking of Passive Sensing and Wireless Communication Spectrum Coexistence," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (Submitted)
- 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, M. Kurum, M. Ogut and A. C. Gurbuz, "Microwave Radiometer Calibration Using Deep Learning With Reduced Reference Information and 2-D Spectral Features," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 17, pp. 748-765, 2024, doi: 10.1109/JSTARS.2023.3333268.
- M. M. Farhad, A. M. Alam, S. Biswas, M. A. S. Rafi, A. C. Gurbuz, and M. Kurum, “Sdr-based dual polarized l-band microwave radiometer operating from small uas platforms,” IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023
- W. Al-Qwider, A. M. Alam, M. Mehedi Farhad, M. Kurum, A. C. Gurbuz and V. Marojevic, "Software Radio Testbed for 5G and L-Band Radiometer Coexistence Research," IGARSS 2023 - 2023 IEEE International Geoscience and Remote Sensing Symposium, Pasadena, CA, USA, 2023, pp. 596-599, doi: 10.1109/IGARSS52108.2023.10283002.