Granted Patent B2

US 12,284,526 · App. 18/802,740 · Granted Apr 22, 2025

Inventors: Armando Montalvo (Winter Garden, FL); Khashayar Kotobi (Tysons Corner, VA)

Assignee: Digital Global Systems, Inc.

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

Abstract

Claims (46)

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

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

a Multi-Access Edge Computing (MEC) layer in a network slice, wherein the MEC layer is in communication with a radio access network (RAN) and a core network; and

at least one data analysis engine in the MEC layer operable to analyze the measured data;

an artificial intelligence (AI) agent in communication with the at least one data analysis engine;

wherein the at least one data analysis engine uses an equalizer to reduce signal interference and/or distortion of at least one signal based on information from at least one other signal for preemptive removal of the at least one other signal before equalization;

wherein the at least one signal and the at least one other signal have a quadrature phase shift keying (QPSK) modulation type; and

wherein the AI agent is operable to make predictions about the electromagnetic environment based on the analyzed data and/or a previous dataset; and

wherein the equalizer is operable to use the predictions about the electromagnetic environment for the equalization and mitigation of signal noise of the at least one signal in real-time as the electromagnetic environment changes.

2. The system of claim 1 , wherein the network slice is administered by a mobile virtual network operator (MVNO).

3. The system of claim 1 , wherein the equalizer reduces the signal interference and/or the distortion of the at least one signal using a Kullback Leibler (KL) Divergence value.

4. The system of claim 1 , wherein the AI agent is operable to utilize at least one AI or machine learning (ML) algorithm to make predictions about the electromagnetic environment.

5. The system of claim 1 , wherein slicing architecture of the MEC layer is based on a plurality of factors including geographic scope, specificity of services, flexible architecture, and/or implementation of MEC applications as part of a slice access point.

6. The system of claim 1 , wherein the AI agent is operable to provide at least one recommendation to optimize L1, L2, and/or L3 network parameters in real time.

7. The system of claim 1 , wherein the equalizer improves the modulation error ratio (MER) of the QPSK modulation type by decreasing the error of the at least one signal.

8. The system of claim 1 , wherein the equalizer utilizes information theory.

9. The system of claim 1 , wherein the AI agent is operable to dynamically suggest changes to network parameters based on at least one customer goal.

10. The system of claim 1 , further comprising at least one radio unit, distributed unit, and/or central unit, wherein at least one of the at least one radio unit, distributed unit, and/or central unit includes the AI agent.

11. The system of claim 1 , wherein the at least one signal and at least one other signal have an overlapping bandwidth.

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

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

a Multi-Access Edge Computing (MEC) layer in a network slice, wherein the MEC layer is in communication with a radio access network (RAN) and a core network; and

at least one data analysis engine in the MEC layer operable to analyze the measured data;

an artificial intelligence (AI) agent in communication with the at least one data analysis engine;

wherein the at least one data analysis engine uses an equalizer to reduce signal interference and/or distortion of at least one signal based on information from at least one other signal for preemptive removal of the at least one other signal before equalization;

wherein the at least one signal and the at least one other signal have a quadrature phase shift keying (QPSK) modulation type;

wherein the AI agent is operable to make predictions about the electromagnetic environment based on the analyzed data and/or a previous dataset;

wherein the equalizer is operable to use the predictions about the electromagnetic environment for the equalization and mitigation of signal noise of the at least one signal in real-time as the electromagnetic environment changes; and

wherein the MEC layer is operable to use the predictions from the AI agent to create actionable data for optimizing network resources.

13. The system of claim 12 , wherein the AI agent is operable to provide at least one recommendation for optimization of L1, L2, and/or L3 parameters.

14. The system of claim 12 , wherein the AI agent is operable to provide at least one recommendation to optimize performance over time based on a training model.

15. The system of claim 12 , wherein the AI agent is operable to provide for validation of sensor fusion based on pattern recognition.

16. The system of claim 12 , wherein the actionable data is based on customer goals.

17. The system of claim 12 , wherein the equalizer utilizes information theory.

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

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

a Multi-Access Edge Computing (MEC) layer in a network slice, wherein the MEC layer is in communication with a radio access network (RAN) and a core network; and

at least one data analysis engine in the MEC layer operable to analyze the measured data;

an artificial intelligence (AI) agent in communication with the at least one data analysis engine;

wherein the at least one data analysis engine uses an equalizer to reduce signal interference and/or distortion of at least one signal based on information from at least one other signal for preemptive removal of the at least one other signal before equalization;

wherein the at least one signal and the at least one other signal have a quadrature phase shift keying (QPSK) modulation type;

wherein the AI agent is operable to make predictions about the electromagnetic environment based on the analyzed data and/or a previous dataset;

wherein the equalizer is operable to use the predictions about the electromagnetic environment for the equalization and mitigation of signal noise of the at least one signal in real-time as the electromagnetic environment changes; and

wherein the AI agent is operable to provide recommendations for optimization of network parameters based on at least one customer goal.

19. The system of claim 18 , wherein the equalizer reduces the signal interference and/or the distortion of at least one signal using a Kullback Leibler (KL) Divergence value.

20. The system of claim 18 , wherein the AI agent is operable to provide at least one recommendation for optimization of L1, L2, and/or L3 network parameters in real time.

Assignments (1)

Continuity (16)

References Cited (232)