US-12627991-B2 - System, method, and apparatus for providing optimized network resources

Abstract

Systems, methods, and apparatuses for providing optimization of network resources. The system is operable to monitor the electromagnetic environment, analyze the electromagnetic environment, and extract environmental awareness of the electromagnetic environment. The system extracts the environmental awareness of the electromagnetic environment by including customer goals. The system is operable to use the environmental awareness with the customer goals and/or user defined policies and rules to extract actionable information to help the customer optimize the network resources.

Inventors

• Armando Montalvo

Assignees

• DIGITAL GLOBAL SYSTEMS, INC.

Dates

Publication Date

20260512

Application Date

20250910

Claims (18)

1. 1 . A system for spectrum utilization management in an electromagnetic environment comprising: a Mult-Access Edge Computing (MEC) layer in a wireless network; at least one data analysis engine in the MEC layer configured to analyze detected signal information from the electromagnetic environment to create measured data; wherein the measured data is represented in a vector ensemble class for each signal in the electromagnetic environment; wherein the data analysis engine is configured to identify information in the measured data relevant to customer goals for a customer application to create analyzed data; a wireless network resource optimization application in the MEC layer; and a machine learning (ML) engine in the MEC layer programmed according to the customer goals; wherein the ML engine is configured to use the analyzed data to make predictions about the electromagnetic environment based on the customer goals and the measured data; and wherein the wireless network resource optimization application is configured to combine the vector ensemble class for each signal in the electromagnetic environment with a customer goals index vector of binary values to create actionable data; wherein each binary value of the customer goals index vector represents whether or not a specific piece of the detected signal information is relevant to satisfying the customer goals; wherein the wireless network resource optimization application is configured to analyze each signal in the electromagnetic environment for possible interactions based on center frequency and a combination of bandwidth and an upper and lower frequency component, and utilize the actionable data, the possible interactions, and the predictions about the electromagnetic environment to optimize network resources of a wireless network for the customer application based on environmental conditions.
2. 2 . The system of claim 1 , wherein the wireless network resource optimization application is configured to further optimize the network resources by reconfiguring the MEC layer associated with a network slice or a subnetwork.
3. 3 . The system of claim 1 , wherein the MEC layer is configured to provide a recommendation for optimization of physical layer resources for the customer application.
4. 4 . The system of claim 1 , wherein the system is configured to perform network slicing to create a network slice.
5. 5 . The system of claim 1 , wherein the wireless network resource optimization application utilizes a constraint vector.
6. 6 . The system of claim 1 , wherein the network resources include physical layer resources.
7. 7 . The system of claim 1 , wherein the network resources include resource blocks, modulation parameters, and/or the bandwidth.
8. 8 . The system of claim 1 , wherein the system includes a MEC host deployed at an edge of a radio access network (RAN).
9. 9 . A system for spectrum utilization management in an electromagnetic environment comprising: a Multi-Access Edge Computing (MEC) layer in a wireless network; a wireless network resource optimization application in the MEC layer including at least one data analysis engine for analyzing detected signal information from a radiofrequency (RF) environment to create measured data; and wherein the measured data is represented in a vector ensemble class for each signal in the RF environment; wherein the data analysis engine is configured to identify information in the measured data relevant to customer goals for a customer application to create analyzed data; a machine learning (ML) engine in the MEC layer programmed according to the customer goals; wherein the detected signal information includes a center frequency, bandwidth, upper frequency component, and lower frequency component of at least one signal in the RF environment; wherein the at least one data analysis engine is configured to analyze each signal in the RF environment to obtain statistical information and analyze possible interactions based on the center frequency, bandwidth, upper frequency component, and lower frequency component to create analyzed data; wherein the ML engine is configured to use the analyzed data to make predictions about the RF environment based on the customer goals and the measured data; wherein the wireless network resource optimization application is configured to combine the vector ensemble class for each signal in the RF environment with a customer goals index vector of binary values to create actionable data; wherein each binary value of the customer goals index vector represents whether or not a specific piece of the detected signal information is relevant to satisfying the customer goals; wherein the wireless network resource optimization application is configured to utilize the actionable data, the possible interactions, and predictions about the RF environment to optimize network resources of a wireless network for the customer application based on environmental conditions.
10. 10 . The system of claim 9 , wherein the wireless network resource optimization application is configured to optimize network resources of a wireless network by reconfiguring the MEC layer associated with a network slice or a subnetwork.
11. 11 . The system of claim 9 , wherein the MEC layer is configured to provide a recommendation for optimization of physical layer resources for the customer application.
12. 12 . A method for spectrum utilization management in an electromagnetic environment comprising: at least one data analysis engine analyzing detected signal information from the electromagnetic environment to create measured data; wherein the measured data is represented in a vector ensemble class for each signal in the electromagnetic environment; the data analysis engine identifying information in the measured data relevant to customer goals for a customer application to create analyzed data; at least one machine learning (ML) engine programmed according to the customer goals and making predictions about the electromagnetic environment based on the customer goals and the measured data; a wireless network resource optimization application analyzing each signal in the electromagnetic environment for possible interactions based on center frequency, and a combination of bandwidth and an upper and lower frequency component; and the wireless network resource optimization application combining the vector ensemble class for each signal in the electromagnetic environment with a customer goals index vector of binary values to create actionable data; wherein each binary value of the customer goals index vector represents whether or not a specific piece of the detected signal information is relevant to satisfying the customer goals; the wireless network resource optimization application utilizing the actionable data, the possible interactions, and the predictions about the electromagnetic environment to optimize network resources of a wireless network for the customer application based on environmental conditions; wherein the at least one data analysis engine, the ML engine, and the wireless network resource optimization application are in a Multi-Access Edge Computing (MEC) layer of a wireless network.
13. 13 . The method of claim 12 , wherein the wireless network resource optimization application is configured to further optimize the network resources by reconfiguring the MEC layer associated with a network slice or a subnetwork.
14. 14 . The method of claim 12 , further comprising the MEC layer providing a recommendation for optimizing physical layer resources for the customer application based on environmental conditions.
15. 15 . The method of claim 12 , wherein the wireless network resource optimization application utilizes a constraint vector.
16. 16 . The method of claim 12 , further comprising a MEC host deployed at an edge of a radio access network (RAN).
17. 17 . The method of claim 12 , wherein the MEC layer creates a network slice.
18. 18 . The method of claim 17 , further comprising performing network slicing to create the network slice.

Description

CROSS REFERENCES TO RELATED APPLICATIONS This application is related to and claims priority from the following U.S. patents and patent applications. This application is a continuation of U.S. application Ser. No. 19/246,025, filed Jun. 23, 2025, which is a continuation of U.S. application Ser. No. 19/005,079, filed Dec. 30, 2024, which is a continuation of U.S. application Ser. No. 18/783,025, filed Jul. 24, 2024, which is a continuation of U.S. patent application Ser. No. 18/428,409, filed Jan. 31, 2024, which is a continuation of U.S. patent application Ser. No. 18/428,373, filed Jan. 31, 2024, which is a continuation of U.S. patent application Ser. No. 18/425,809, filed Jan. 29, 2024, which is a continuation of U.S. patent application Ser. No. 18/415,174, filed Jan. 17, 2024, which is a continuation of U.S. patent application Ser. No. 18/336,462, filed Jun. 16, 2023, which is a continuation of U.S. patent application Ser. No. 18/101,899, filed Jan. 26, 2023, which is a continuation of U.S. patent application Ser. No. 17/901,035, filed Sep. 1, 2022, which claims priority to and the benefit of U.S. Provisional Patent Application No. 63/370,184, filed Aug. 2, 2022, each of which is incorporated herein by reference in its entirety. BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to spectrum analysis and management for electromagnetic signals, and more particularly for providing optimized network resources. 2. Description of the Prior Art It is generally known in the prior art to provide wireless communications spectrum management for detecting devices and for managing the space. Spectrum management includes the process of regulating the use of radio frequencies to promote efficient use and gain net social benefit. A problem faced in effective spectrum management is the various numbers of devices emanating wireless signal propagations at different frequencies and across different technological standards. Coupled with the different regulations relating to spectrum usage around the globe effective spectrum management becomes difficult to obtain and at best can only be reached over a long period of time. Another problem facing effective spectrum management is the growing need from spectrum despite the finite amount of spectrum available. Wireless technologies and applications or services that require spectrum have exponentially grown in recent years. Consequently, available spectrum has become a valuable resource that must be efficiently utilized. Therefore, systems and methods are needed to effectively manage and optimize the available spectrum that is being used. Prior art patent documents include the following: U.S. Pat. No. 11,395,149 for System, method, and apparatus for providing dynamic, prioritized spectrum management and utilization by inventor Montalvo, filed Oct. 30, 2020 and issued Jul. 19, 2022, is directed to 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. U.S. Patent Publication No. 2018/0352441 for Devices, methods, and systems with dynamic spectrum sharing by inventors Zheng, et al., filed Jun. 4, 2018 and published Dec. 6, 2018, is directed to devices, methods, and systems with dynamic spectrum sharing. A wireless communication device includes a software-defined radio, a spectrum sensing sub-system, a memory, and an electronic processor. The software-defined radio is configured to generate an input signal, and wirelessly communicate with one or more radio nodes using a traffic data channel and a broadcast control channel. The spectrum sensing sub-system is configured to sense local spectrum information from the input signal. The electronic processor is communicatively connected to the memory and the spectrum sensing sub-system and is configured to receive the local spectrum information from the spectrum sensing sub-system, receive spectrum information from the one or more radio nodes, and allocate resources for the traffic data channel based on the local spectrum information and the spectrum information that is received from the one or more radio nodes. U.S. Patent Publication No. 2018/0295607 for Method and apparatus for adaptive bandwidth usage in a wireless communication network by inventors Lindoff, et al., filed Oct. 10, 2017 and published Oct. 11, 2018, is directed to reconfiguration of a receiver bandwidth of the wireless device is initiated to match the second scheduling bandwidth, wherein the second scheduling bandwidth is larger than a first scheduling bandwidth currently associat