Deterministic Move Lists for Federal Incumbent Protection in the CBRS Band

IF 7.4 1区计算机科学 Q1 TELECOMMUNICATIONS

IEEE Transactions on Cognitive Communications and Networking Pub Date : 2020-10-13 DOI:10.1109/TCCN.2020.3030643

Thao T. Nguyen;Michael R. Souryal

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引用次数: 2

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. To protect the federal incumbents from harmful interference, a spectrum access system (SAS) is required to use a common, standardized algorithm, called 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 used for SAS testing is non-deterministic in that it uses a Monte Carlo estimate of the

$95^{\mathrm {th}}$

percentile of the aggregate interference from CBSDs to the incumbent. This leads to uncertainty in move list results and in the aggregate interference check of the test. This article uses upper and lower bounds on the aggregate interference distribution to compute deterministic move lists. These include the reference move list used by the testing system and an operational move list used by the SAS itself. 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.

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联邦在职人员在CBRS波段保护的确定性移动列表

美国的3.5 GHz公民宽带无线电服务（CBRS）频段是商业运营商与现有联邦和非联邦现有运营商共享的中频频谱的关键部分。为了保护联邦现任者免受有害干扰，频谱接入系统（SAS）需要使用一种通用的标准化算法，称为移动列表算法，以暂停某些CBRS设备（CBSD）在现任者活跃的信道上的传输。然而，用于SAS测试的当前参考移动列表实现是不确定的，因为它使用了从CBSD到现任者的总干扰的$95 ^｛\mathrm｛th｝｝$百分位数的蒙特卡罗估计。这导致移动列表结果和测试的总干扰检查中存在不确定性。本文使用聚合干扰分布的上界和下界来计算确定性移动列表。其中包括测试系统使用的参考移动列表和SAS本身使用的操作移动列表。我们使用标准的参考实现和联邦现任动态保护区附近的模拟CBSD部署来评估所提出的确定性移动列表的性能。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Cognitive Communications and Networking Computer Science-Artificial Intelligence

CiteScore

15.50

自引率

7.00%

发文量

108

期刊介绍： The IEEE Transactions on Cognitive Communications and Networking (TCCN) aims to publish high-quality manuscripts that push the boundaries of cognitive communications and networking research. Cognitive, in this context, refers to the application of perception, learning, reasoning, memory, and adaptive approaches in communication system design. The transactions welcome submissions that explore various aspects of cognitive communications and networks, focusing on innovative and holistic approaches to complex system design. Key topics covered include architecture, protocols, cross-layer design, and cognition cycle design for cognitive networks. Additionally, research on machine learning, artificial intelligence, end-to-end and distributed intelligence, software-defined networking, cognitive radios, spectrum sharing, and security and privacy issues in cognitive networks are of interest. The publication also encourages papers addressing novel services and applications enabled by these cognitive concepts.