In the United States, the Federal Communications Commission has adopted rules permitting commercial wireless networks to share spectrum with federal incumbents in the 3.5 GHz Citizens Broadband Radio Service band. These rules require commercial systems to vacate the band when sensors detect radars operated by the U.S. military; a key example being the SPN-43 air traffic control radar. Such sensors require highly-accurate detection algorithms to meet their operating requirements. In this paper, using a library of over 14,000 3.5 GHz band spectrograms collected by a recent measurement campaign, we investigate the performance of thirteen methods for SPN-43 radar detection. Namely, we compare classical methods from signal detection theory and machine learning to several deep learning architectures. We demonstrate that machine learning algorithms appreciably outperform classical signal detection methods. Specifically, we find that a three-layer convolutional neural network offers a superior tradeoff between accuracy and computational complexity. Last, we apply this three-layer network to generate descriptive statistics for the full 3.5 GHz spectrogram library. Our findings highlight potential weaknesses of classical methods and strengths of modern machine learning algorithms for radar detection in the 3.5 GHz band.
The mission of the National Advanced Spectrum and Communications Test Network (NASCTN) is to provide, through its members, robust test processes and validated measurement data necessary to develop, evaluate and deploy spectrum sharing technologies that can increase access to the spectrum by both federal agencies and non-federal spectrum users.The U.S. Department of Commerce's National Institute of Standards and Technology (NIST) and National Telecommunications and Information Administration (NTIA) established the Center for Advanced Communications (CAC) in Boulder, Colorado, to address, among other challenges, the increasing need for spectrum sharing testing and evaluation capabilities to meet national needs. As part of CAC's mission to provide a single focal point for engaging both industry and other government agencies on advanced communication technologies, including testing, validation, and conformity assessment, NASCTN was formed under the umbrella of the CAC. NIST hosts the NASCTN capability at the Department of Commerce Boulder Laboratories in Boulder, Colorado. NASCTN is a membership organization under a charter agreement. Members• Make available, in accordance with their organization's rules policies and regulations, engineering capabilities and test facilities, with typical consideration for cost.• Coordinate their efforts to identify, develop and test spectrum sharing ideas, concepts and technology to support the goal of advancing more efficient and effective spectrum sharing.• Make available information related to spectrum sharing, considering requirements for the protection of intellectual property, national security, and other organizational controls, and, to the maximum extent possible, allow the publication of NASCTN test results.• Ensure all spectrum sharing efforts are identified to other interested members.Current charter members are:• National Telecommunications and Information Administration (NTIA)• National Institute of Standards and Technology (NIST)• Department of Defense Chief Information Officer (DoD CIO) AcknowledgmentsWe thank the Department of Defense and Space and Naval Warfare (SPAWAR) Systems Center Pacific for providing access to the measurement site at Point Loma; Michael Cotton and his colleagues at the National Telecommunications and Information Administration (NTIA), Institute for Telecommunications Sciences (ITS), Boulder, Colorado, for the use of the pre-selector; Frank Sanders at NTIA/ITS for sharing his expertise on radar systems and measurements; John Ladbury at NIST for characterizing the antennas we used in our measurements; and the NASCTN staff for stakeholder management, project management, and coordination.iii ______________________________________________________________________________________________________ This publication is available free of charge from: https://doi.org/10.6028/NIST. TN.1954 iv ______________________________________________________________________________________________________ This publication is available free of charge from: https://do...
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