Granted Patent B2

US 12,273,734 · App. 18/911,916 · Granted Apr 8, 2025

Inventors: Armando Montalvo (Winter Garden, FL); Dwight Inman (Travelers Rest, SC); Edward Hummel (Hillsborough, NJ)

Assignee: Digital Global Systems, Inc.

H04W16/14G06F30/27G06N3/02G06N5/022G06N5/04G06N20/00G06N20/10G06N20/20H04L41/0893H04L41/16H04W16/10H04W24/02H04W72/0453G06N3/042G06N3/045H04L41/0894H04W24/08Y04S40/00

Abstract

Claims (50)

1. A system for dynamic, prioritized spectrum utilization management in an electromagnetic environment comprising:

at least one monitoring sensor operable to monitor the electromagnetic environment, thereby creating measured data;

at least one data analysis engine for analyzing the measured data to create analyzed data;

at least one survey occupancy application; and

at least one server;

wherein the at least one monitoring sensor includes an antenna array formed of multiple antennas resonating at different frequency bands and configured in a 1D (linear), 2D (planar), or 3D antenna configuration;

wherein the at least one survey occupancy application is operable to schedule occupancy in at least one frequency band;

wherein the at least one server is in communication with the at least one data analysis engine and the at least one survey occupancy application;

wherein the at least one server is operable to use the analyzed data to create actionable data;

wherein the system is operable to use machine learning (ML) to create prediction models to autonomously create forecasts for future spectrum usage based on historical data and the analyzed data; and

wherein the survey occupancy application is operable to use the actionable data and a priority assigned to at least one customer application to dynamically allocate the at least one frequency band in the electromagnetic spectrum.

2. The system of claim 1 , wherein the at least one monitoring sensor includes at least one antenna, at least one antenna array, at least one radio server, and/or at least one software defined radio.

3. The system of claim 1 , wherein the at least one survey occupancy application is operable to preprocess at least two signals that exist in the at least one frequency band based on interference between the at least two signals.

4. The system of claim 1 , wherein the survey occupancy application further uses a priority assigned to at least one customer application to dynamically allocate the at least one frequency band in the electromagnetic spectrum.

5. The system of claim 1 , further comprising a certification and compliance application, wherein the certification and compliance application is operable to determine if at least one customer application and/or at least one customer device is behaving according to at least one rule and/or at least one policy.

6. The system of claim 1 , wherein the at least one survey occupancy application is operable to determine occupancy in frequency bands.

7. The system of claim 1 , further comprising a learning engine 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.

8. The system of claim 1 , wherein the at least one survey occupancy application is operable to determine occupancy in the at least one frequency band.

9. A system for dynamic, prioritized spectrum utilization management in an electromagnetic environment comprising:

at least one monitoring sensor operable to monitor the electromagnetic environment, thereby creating measured data;

at least one data analysis engine for analyzing the measured data to create analyzed data;

at least one server; and

at least one survey occupancy application;

wherein the at least one monitoring sensor includes an antenna array formed of multiple antennas resonating at different frequency bands and configured in a 1D (linear), 2D (planar), or 3D (area) antenna configuration;

wherein the at least one data analysis engine is operable to automatically detect at least one signal of interest and learn the electromagnetic environment based on the analyzed data;

wherein the at least one survey occupancy application is operable to determine occupancy in frequency bands;

wherein the at least one server is operable to use the analyzed data from the at least one data analysis engine to create actionable data;

wherein the at least one survey occupancy application is operable to schedule occupancy in at least one frequency band;

wherein the system is operable to use machine learning (ML) to create prediction models to autonomously create forecasts for future spectrum usage based on historical data and the analyzed data;

wherein at least one customer application is assigned a priority; and

wherein the priority is used to allocate the at least one frequency band in the electromagnetic spectrum.

10. The system of claim 9 , wherein the at least one survey occupancy application is operable to schedule occupancy in at least one frequency band.

11. The system of claim 9 , further comprising a learning engine 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.

12. The system of claim 9 , wherein the system further includes a certification and compliance application, wherein the certification and compliance application is operable to determine if the at least one customer application and/or at least one customer device is behaving according to at least one rule and/or at least one policy.

13. The system of claim 9 , wherein the at least one survey occupancy application is operable to preprocess at least two signals that exist in the at least one frequency band based on interference between the at least two signals.

14. A method for dynamic, prioritized spectrum utilization management in an electromagnetic environment comprising:

monitoring the electromagnetic environment using at least one monitoring sensor, thereby creating measured data;

analyzing the measured data using at least one data analysis engine, thereby creating analyzed data;

determining occupancy in at least one frequency band using a survey occupancy application;

scheduling occupancy in the at least one frequency band using the at least one survey occupancy application;

creating prediction models to autonomously create forecasts for future spectrum usage based on historical data and the analyzed data;

assigning a priority to at least one customer application; and

dynamically allocating the at least one frequency band in the electromagnetic spectrum based on the priority;

wherein the at least one monitoring sensor includes an antenna array formed of multiple antennas resonating at different frequency bands and configured in a 1D (linear), 2D (planar), or 3D antenna configuration.

15. The method of claim 14 , further comprising scheduling occupancy in the at least one frequency band using the survey occupancy application.

16. The method of claim 14 , wherein the survey occupancy application preprocess at least two signals that exist in the at least one frequency band based on interference between the at least two signals.

17. The method of claim 14 , further including a certification and compliance application determining if at least one customer application and/or at least one customer device is behaving according to at least one rule and/or at least one policy.

18. The method of claim 14 , wherein the at least one monitoring sensor includes at least one antenna, at least one antenna array, at least one radio server, and/or at least one software defined radio.

19. The method of claim 14 , further comprising 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.

20. The method of claim 14 , further comprising determining an impact of interference on customer goals and/or customer operations and allocating the at least one frequency band in the electromagnetic spectrum based on the determined impact of the interference.

Assignments (1)

Continuity (11)

References Cited (400)

Cited By (2)

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