Geospatial Cognitive Networking Protocols and Sensing Algorithms for 5G NR Beamforming

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Geospatial_Cognitive_Networking_Protocols_and_Sensing_Algorithms_for_5G_NR_Beamforming.pdf (2.66 MB)

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https://ieeexplore.ieee.org/abstract/document/9878144

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https://doi.org/10.1109/TCCN.2022.3204536
 http://hdl.handle.net/11603/26142

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UMBC Computer Science and Electrical Engineering Department
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https://orcid.org/0000-0002-7627-1478
 https://orcid.org/0000-0003-3865-9217

Date

2022-09-06

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journal articles
postprints
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Citation of Original Publication

B. W. Stevens and M. F. Younis, "Geospatial Cognitive Networking Protocols and Sensing Algorithms for 5G NR Beamforming," in IEEE Transactions on Cognitive Communications and Networking, 2022, doi: 10.1109/TCCN.2022.3204536.

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Abstract

Although 5G New Radio (NR) has created new opportunities for cognitive radio networks, its increased physical layer security and flexibility limit the usefulness of traditional cognitive detectors such as energy and blind control channel algorithms. This paper presents CASINO-NR, a novel framework for establishing a cognitive self-reliant secondary network with no additional physical infrastructure, collaboration from the primary network nodes, and software or hardware changes to the existing 5G network. CASINO-NR includes a novel beam detection algorithm that finds and ranks 5G NR synchronization signals to determine geospatially non-interfering beams for secondary communications. We compare the developed beam detector with multiple existing approaches for sensitivity to interference and phase distortions. We also apply power control to prevent interference on neighboring beams. CASINO-NR is analyzed against the estimated throughput capacity and capabilities of other cognitive detectors found in literature. Finally, we examine an experimental beamforming example to demonstrate our beam detection algorithm and present a case for geospatial resources for cognitive radio communications.