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Deterministic Move Lists for Federal Incumbent Protection in the CBRS Band

Published

Author(s)

Michael R. Souryal, Thao T. Nguyen

Abstract

The 3.5 GHz citizens broadband radio service (CBRS) band in the U.S. is a key portion of mid- band spectrum shared between commercial operators and existing federal and non-federal incumbents in the band. To protect the federal incumbents from harmful interference, a spectrum access system (SAS) is required to use a common, standardized algorithm, referred to as the move list algorithm, to suspend transmissions of some CBRS devices (CBSDs) on channels in which the incumbent becomes active. However, the current reference move list implementation—for testing SAS compliance with federal incumbent protection requirements—is non-deterministic in that it uses a Monte Carlo estimate of the 95th percentile of the aggregate interference from CBSDs to the protected entity. This leads to uncertainty in move list results as well as in the aggregate interference check of the "keep list," the complement of the move list. The objective of this paper is to utilize upper and lower bounds on the aggregate interference distribution to compute deterministic move lists. These include the reference move list for testing the SAS and an operational move list that a SAS might use in commercial operations. We evaluate the performance of the proposed deterministic move lists using reference implementations of the standards and simulated CBSD deployments in the vicinity of federal incumbent dynamic protection areas (DPAs). Although bounds do not provide exact results, they can be beneficial in reducing the computational complexity and uncertainty associated with Monte Carlo approaches, especially in a multi-SAS environment.
Citation
IEEE Transactions on Cognitive Communications and Networking

Keywords

3.5 GHz, CBRS, incumbent protection, aggregate interference, move list

Citation

Souryal, M. and Nguyen, T. (2020), Deterministic Move Lists for Federal Incumbent Protection in the CBRS Band, IEEE Transactions on Cognitive Communications and Networking, [online], https://doi.org/10.1109/TCCN.2020.3030643, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=930112 (Accessed May 17, 2022)
Created October 12, 2020, Updated October 12, 2021