Granted Patent B2

US 12,309,598 · App. 18/813,985 · Granted May 20, 2025

Inventor: Armando Montalvo (Winter Garden, FL)

Assignee: Digital Global Systems, Inc.

H04W16/10H04W24/02H04W24/08H04W28/0925H04W28/0967H04W72/0453H04W16/14

Abstract

Claims (50)

1. A system for optimization of spectrum utilization in an electromagnetic environment, comprising:

at least one monitoring sensor operable to monitor the electromagnetic environment and to create measured data;

at least one data analysis engine operable to analyze the measured data to create analyzed data;

at least one server configured to enable communication over a network;

at least one interference mitigation engine; and

at least one multi-network orchestration module;

wherein the at least one data analysis engine is operable to generate and select at least one parameter to store in a parameter block based on the measured data;

wherein the at least one data analysis engine includes an embedded artificial intelligence (AI) agent;

wherein the embedded AI agent is operable to receive the at least one parameter from the data analysis engine;

wherein the embedded AI agent is operable to dynamically adjust the at least one parameter based on at least one customer goal;

wherein the embedded AI agent is operable to make predictions and about the electromagnetic environment based on the analyzed data;

wherein the embedded AI agent is operable to utilize and apply control theory and statistical learning techniques to the analyzed data to optimize Layer 1 (L1), Layer 2 (L2), and Layer 3 (L3) network parameters and functions;

wherein the at least one interference mitigation engine operable to use analyzed data to identify and mitigate interference between at least two wireless signals transmitted on overlapping frequency bands; and

wherein the at least one multi-network orchestration module operable to manage simultaneous operation of at least two wireless networks that contain the at least two wireless signals.

2. The system of claim 1 , wherein the embedded AI agent is operable to utilize AI and/or machine learning (ML) to dynamically adjust to the at least one parameter.

3. The system of claim 1 , wherein the at least one interference mitigation engine utilizes AI and/or machine learning (ML) to predict interference patterns between the at least two wireless networks.

4. The system of claim 1 , wherein the at least two wireless signals include at least one 4G, 5G, and/or 6G signal.

5. The system of claim 1 , wherein the at least one interference mitigation engine is in communication with the embedded AI agent.

6. The system of claim 1 , wherein the at least one multi-network orchestration module is operable to prioritize network traffic based on demand.

7. The system of claim 1 , wherein the at least one multi-network orchestration module allocates spectrum resources based on real-time network traffic demands and quality of service (QOS) requirements.

8. The system of claim 1 , further comprising at least one smart contract engine that utilizes blockchain technology to facilitate dynamic spectrum leasing and sharing between at least two telecommunication operators.

9. A system for optimization of spectrum utilization in an electromagnetic environment, comprising:

at least one monitoring sensor operable to monitor an electromagnetic environment and to create measured data;

at least one multi-network orchestration module; and

at least one data analysis engine operable to analyze the measured data to create analyzed data;

wherein the at least one data analysis engine is operable to generate and select at least one parameter to store in a parameter block based on the measured data;

wherein the at least one data analysis engine includes a Fast Fourier Transform (FFT) engine operable to provide for a duty cycle using four streams and one second per stream to reduce calculations and provide for increased real-time sampling;

wherein the at least one data analysis engine includes an embedded artificial intelligence (AI) agent operable to receive the at least one parameter from the data analysis engine;

wherein the embedded AI agent includes at least one training model operable to recognize patterns and trends based on the analyzed data;

wherein the embedded AI agent dynamically adjusts network allocation based on the at least one training model; and

wherein the at least one multi-network orchestration module is operable to manage simultaneous allocation of at least two wireless networks.

10. The system of claim 9 , wherein the analyzed data includes at least one wireless signal.

11. The system of claim 9 , further comprising at least one smart contract engine operable to facilitate dynamic spectrum leasing between at least two telecommunication operators.

12. The system of claim 11 , wherein the at least two wireless networks contain at least two wireless signals.

13. The system of claim 9 , further comprising a user-centric spectrum management module operable to personalize network performance enhancements.

14. The system of claim 13 , wherein the personalized network enhancements are based on at least one user need.

15. The system of claim 14 , wherein the at least one user need includes low-latency connections and/or high-bandwidth requirements.

16. A method for optimization of spectrum utilization in an electromagnetic environment comprising:

monitoring the electromagnetic environment to create measured data with at least one monitoring sensor;

analyzing the measured data to create analyzed data including at least two wireless signals with at least one data analysis engine;

generating and selecting at least one parameter to store in a parameter block based on the measured data with the at least one data analysis engine;

dynamically adjusting at least one training model based on feedback from the electromagnetic environment using an embedded artificial intelligence (AI) agent of the at least one data analysis engine;

dynamically adjusting the at least one parameter to optimize performance of the at least two wireless signals with the embedded AI agent;

identifying and mitigating interference between the at least two wireless signals transmitted on overlapping frequency bands with at least one interference mitigation engine based on a communication from the embedded AI agent; and

managing simultaneous operation of at least two wireless networks containing the at least two wireless signals with at least one multi-network orchestration module;

wherein the at least one data analysis engine includes a Fast Fourier Transform (FFT) engine providing for a duty cycle using four streams and one second per stream to reduce calculations and provide for increased real-time sampling.

17. The method of claim 16 , wherein the embedded AI agent utilizes at least one AI algorithm and/or machine learning (ML) algorithm to refine the training model and adjust the at least one parameter.

18. The method of claim 17 , wherein the embedded AI agent learns from previous spectrum allocation decisions.

19. The method of claim 16 , further comprising at least one smart contract engine managing dynamic spectrum leasing between at least two telecommunication operators.

20. The method of claim 19 , wherein the at least two telecommunication operators share spectrum resources.

Assignments (1)

Continuity (16)

References Cited (236)

Cited By (2)

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