IP Library Granted Patent US 11,924,648
Granted Patent B1
US 11,924,648 · App. 18/503,640 · Granted Mar 5, 2024

System, method, and apparatus for providing dynamic, prioritized spectrum management and utilization

Inventors: Armando Montalvo (Winter Garden, FL); Dwight Inman (Travelers Rest, SC); Edward Hummel (Hillsborough, NJ)
Assignee: DIGITAL GLOBAL SYSTEMS, INC.
H04W16/10G06F30/27G06N3/02G06N5/022G06N5/04G06N20/00G06N20/10G06N20/20H04L41/0893H04W24/02H04W72/0453G06N3/042G06N3/045H04L41/0894H04W16/14H04W24/08
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Quick Facts
Patent No.
US 11,924,648
App. No.
18/503,640
Granted
Mar 5, 2024
Kind
B1
Abstract

Systems, methods, and apparatuses for providing dynamic, prioritized spectrum utilization management. The system includes at least one monitoring sensor, at least one data analysis engine, at least one application, a semantic engine, a programmable rules and policy editor, a tip and cue server, and/or a control panel. The tip and cue server is operable utilize the environmental awareness from the data processed by the at least one data analysis engine in combination with additional information to create actionable data.

Claims (37)

1. A system for spectrum management in an electromagnetic environment comprising:

at least one sensor operable for receiving data associated with at least one signal in the electromagnetic environment;

at least one data analysis engine for analyzing the data, wherein the at least one data analysis engine includes at least two of: a detection engine, an identification engine, and a learning engine;

wherein the detection engine is operable to automatically detect the at least one signal;

wherein the identification engine uses signal profiling and/or comparison with at least one previously recorded signal profile in a database to identify the at least one signal as interference;

wherein the learning engine receives information from the detection engine and the identification engine; and

wherein the learning engine is operable to learn the electromagnetic environment using machine learning (ML), artificial intelligence (AI), deep learning (DL), neural networks (NNs), artificial neural networks (ANNs), support vector machines (SVMs), Markov decision process (MDP), natural language processing (NLP), control theory, and/or statistical learning techniques;

thereby providing analyzed data that is actionable for managing the electromagnetic environment in real time or near real time.

2. The system of claim 1 , further including a customer optimization module that is operable to discern an impact of the interference on other signals in the electromagnetic environment.

3. The system of claim 1 , further including a customer optimization module that is operable to discern an impact of the interference on other signals in the electromagnetic environment, including predefined customer goals and/or customer operations.

4. The system of claim 1 , further including a customer optimization module that is operable to discern an impact of the interference on other signals in the electromagnetic environment; and further operable to send actionable data related to the electromagnetic environment to an operational engine.

5. The system of claim 1 , further including a survey occupancy application, wherein the survey occupancy application is operable to determine occupancy in frequency bands and to manage occupancy in at least one frequency band based on the analyzed data.

6. The system of claim 1 , wherein the system is operable to activate at least one alarm and/or provide at least one notification based on the analyzed data and detection of the interference.

7. The system of claim 1 , wherein the system is operable to provide an alert relating to interference between a first signal and at least one second signal.

8. The system of claim 7 , wherein the system is operable to identification of a resolution to the first signal and/or a base station associated with the at least one first signal, wherein the resolution includes modification of parameters to resolve the interference.

9. The system of claim 1 , wherein the identification of the at least one signal is performed autonomously.

10. The system of claim 1 , wherein the system is operable to provide an automated report relating to the identification of the at least one signal.

11. The system of claim 1 , wherein the system is further operable to maintain a set of de-confliction rules usable to resolve the interference.

12. The system of claim 1 , further comprising at least one classification engine operable to correlate the at least one signal with known signal protocols, correlate the at least one signal with known variables, correlate the at least one signal with known databases, correlate the at least one signal with existing wireless signal formats, and/or correlate the at least one signal with existing cellular protocol formats, and wherein the at least one classification engine is trained to correlate the at least one signal with known signal protocols, correlate the at least one signal with known variables, correlate the at least one signal with known databases, correlate the at least one signal with existing wireless signal formats, and/or correlate the at least one signal with existing cellular protocol formats based on at least one neural network.

13. A method for spectrum management in an electromagnetic environment comprising:

at least one sensor receiving data associated with at least one signal in the electromagnetic environment;

at least one data analysis engine analyzing the data, wherein the at least one data analysis engine includes at least two of: a detection engine, an identification engine, and a learning engine;

the detection engine automatically detecting the at least one signal;

the identification engine using signal profiling and/or comparison with at least one previously recorded signal profile in a database and identifying the at least one signal as interference;

the learning engine receiving information from the detection engine and the identification engine; and

the learning engine learning the electromagnetic environment using machine learning (ML), artificial intelligence (AI), deep learning (DL), neural networks (NNs), artificial neural networks (ANNs), support vector machines (SVMs), Markov decision process (MDP), natural language processing (NLP), control theory, and/or statistical learning techniques; and

providing analyzed data that is actionable for managing the electromagnetic environment in real time or near real time.

14. The method of claim 13 , further including the step of: a customer optimization module indicating an impact of the interference on other signals in the electromagnetic environment.

15. The method of claim 13 , further including the step of: a customer optimization module indicating an impact of the interference on other signals in the electromagnetic environment, the impact based on predefined customer goals and/or customer operations.

16. The method of claim 13 , further including the step of: a customer optimization module identifying an impact of the interference on other signals in the electromagnetic environment and communicating actionable data related to the electromagnetic environment to an operational engine.

17. The method of claim 13 , further including the step of: a survey occupancy application determining occupancy in frequency bands.

18. The method of claim 17 , further including the step of: the survey occupancy application managing occupancy in at least one frequency band based on the analyzed data.

19. The method of claim 13 , further including the step of: the system activating at least one alarm and/or providing at least one notification based on the analyzed data and detection of the interference.

20. The method of claim 13 , further including the step of: providing an alert relating to interference between a first signal and at least one second signal.

21. The method of claim 20 , wherein the system is operable to identify a resolution to the first signal and/or a base station associated with the first signal, wherein the resolution includes the step of modifying parameters to resolve the interference.

22. The method of claim 13 , wherein the identification of the at least one signal is performed autonomously.

23. The method of claim 13 , further including providing an automated report relating to the identification of the at least one signal.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 20, 2023
From: MONTALVO, ARMANDO; INMAN, DWIGHT; HUMMEL, EDWARD
To: DIGITAL GLOBAL SYSTEMS, INC.
Reel/Frame 065624/0192 →
Continuity (6)
Continuation 18201383 · May 24, 2023
Continuation 18081331 · Dec 14, 2022
Continuation 17901330 · Sep 1, 2022
Continuation 17461267 · Aug 30, 2021
Continuation 17085635 · Oct 30, 2020
Provisional Application 63018929 · May 1, 2020
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