Invention Grant
- Patent Title: Monitoring a cellular wireless network for a spectral anomaly and training a spectral anomaly neural network
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Application No.: US17003637Application Date: 2020-08-26
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Publication No.: US11647401B2Publication Date: 2023-05-09
- Inventor: Meik Kottkamp , Andreas Roessler , Reiner Stuhlfauth , Holger Rosier
- Applicant: Rohde & Schwarz GmbH & Co. KG
- Applicant Address: DE Munich
- Assignee: ROHDE & SCHWARZ GMBH & CO. KG
- Current Assignee: ROHDE & SCHWARZ GMBH & CO. KG
- Current Assignee Address: DE Munich
- Agency: Ditthavong, Steiner & Mlotkowski
- Priority: EP 206494 2019.10.31
- Main IPC: H04W24/02
- IPC: H04W24/02 ; H04W24/08 ; H04L25/02 ; G06N3/08 ; G06N20/00 ; H04B17/10 ; H04L25/03 ; H04W24/10

Abstract:
A monitoring system and monitoring method for detecting a spectral anomaly in a cellular wireless network, in particular a 5G private uRLLC network, wherein an RF receiver monitors the cellular wireless network spectrum and derives spectrum and/or physical measurement values of the spectrum of the cellular wireless network, and a processing unit of the monitoring system executes a spectral anomaly neural network trained by a machine learning algorithm in a training system, wherein the processing unit obtains the spectrum and/or the physical measurement values of the spectrum and processes it to detect a spectral anomaly information. Further, a training system and training method for training a spectral anomaly neural network, wherein the training system/method is used in a cellular wireless network, in particular a 5G private uRLLC network, and an RF receiver of the training system monitors the cellular wireless network spectrum and derives spectrum and/or physical measurement values of the spectrum of the cellular wireless network, and a processor of the training system executes a machine learning algorithm to train the spectral anomaly neural network based upon the derived spectrum and/or physical measurement values of the spectrum of the cellular wireless network.
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