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Emerging communication services and satellite system deployments pose heightened interference challenges for crucial passive radiometer sensors used in environmental and atmospheric sensing. Therefore, there is an urgent necessity to develop effective approaches for detecting, mitigating, and characterizing the influence of anthropogenic sources, commonly referred to as radio frequency interference (RFI) on passive Earth-observing microwave radiometers. Experimenting the co-existence of active communication and passive sensing systems would greatly benefit from a thorough and realistic dataset covering a wide range of scenarios. The insufficient availability of extensive datasets in the radio frequency (RF) domain, particularly in the context of active/passive coexistence, poses a significant obstacle to progress. This limitation is particularly notable in the context of comprehending the effectiveness of conventional model-based RFI detection approaches when applied to advanced 5th-generation (5G) wireless communication signals. This study first shows the development of an experimental passive radiometer and 5G testbed system and aims to assess the efficacy of the widely employed spectral kurtosis RFI detection approach within controlled anechoic chamber experiments. Our experimental setup comprises a fully calibrated SDR-based L-band radiometer subjected to diverse 5 G wireless signals, varying in power levels, frequency resource block group allocation, and modulation techniques. Significantly, our testbed facilitates the concurrent recording of ground truth temperatures while subjecting the radiometer to 5 G signal transmission which helps to understand the overall effect in the radiometer. This distinctive configuration provides insights into the effectiveness of traditional RFI detection models, offering valuable perspectives on the associated challenges in RFI detection.
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Dataset for Spectrum Coexistence in Passive Sensing and Wireless Communication
In our ever-expanding world of advanced satellite and communications systems, there's a growing challenge for passive radiometer sensors used in the Earth observation like 5G. These passive sensors are challenged by risks from radio frequency interference (RFI) caused by anthropogenic signals. To address this, we urgently need effective methods to quantify the impacts of 5G on Earth observing radiometers. Unfortunately, the lack of substantial datasets in the radio frequency (RF) domain, especially for active/passive coexistence, hinders progress. Our study introduces a controlled testbed featuring a calibrated L-band radiometer and a 5G wireless communication system. In a controlled chamber, this unique setup allows us to observe and quantify transmission effects across different frequency bands. By creating a comprehensive dataset, we aim to standardize and benchmark both wireless communication and passive sensing. With the ability to analyze raw measurements, our testbed facilitates RFI detection and mitigation, fostering the coexistence of wireless communication and passive sensing technologies while establishing crucial standards.
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- PAR ID:
- 10559320
- Publisher / Repository:
- IEEE DataPort
- Date Published:
- Subject(s) / Keyword(s):
- L-band radiometer 5G Mobile Communications 5G New Radio Cellular Measurements Coverage Extension Packet Capture Video Streaming Wireless Communications Earth observation Artificial Intelligence Big Data Dataset Machine Learning dataset
- Format(s):
- Medium: X
- Right(s):
- Creative Commons Attribution 4.0 International
- Sponsoring Org:
- National Science Foundation
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