System, method, and apparatus for providing optimized network resources
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.
1. A system for dynamic spectrum utilization management in an electromagnetic environment comprising:
at least one monitoring sensor operable to monitor the electromagnetic environment and to create measured data;
a Multi-Access Edge Computing (MEC) layer in a network slice or a subnetwork, wherein the MEC layer is in communication with a radio access network (RAN) and a core network; and
a wireless network resource optimization application in the MEC layer, wherein the wireless network resource optimization application includes at least one data analysis engine for analyzing the measured data and a programmable rules and policy editor;
wherein the at least one data analysis engine includes a detection engine and a learning engine, wherein the detection engine is operable to automatically detect at least one signal of interest, and wherein the learning engine is operable to learn the electromagnetic environment;
wherein the programmable rules and policy editor includes at least one rule and/or at least one policy; and
wherein the wireless network resource optimization application is operable to use analyzed data from the at least one data analysis engine to create actionable data for optimizing network resources.
2. The system of claim 1 , wherein the network resources are optimized by reconfiguring the core network and/or the MEC associated with the network slice or the subnetwork.
3. The system of claim 1 , wherein the network resources are optimized by changing physical layer parameters of one or more customer devices and/or applications.
4. The system of claim 1 , wherein the at least one monitoring sensor is in communication with the MEC layer, wherein the at least one monitoring sensor is included in a base station and/or at least one spectrum monitoring unit, wherein the at least one spectrum monitoring unit includes a housing, at least one processor and memory, at least one receiver, and the at least one monitoring sensor.
5. 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.
6. The system of claim 1 , wherein one or more of the at least one rule and/or the at least one policy is defined by requirements of at least one customer.
7. The system of claim 1 , wherein the wireless network resource optimization application is operable to activate an alarm.
8. The system of claim 1 , wherein the at least one data analysis engine further includes an identification engine, a classification engine, and/or a geolocation engine.
9. The system of claim 1 , wherein the wireless network resource optimization application generates at least one RAN command to change at least one RAN parameter.
10. The system of claim 1 , wherein the wireless network resource optimization application creates a vector ensemble class for the at least one signal of interest.
11. The system of claim 10 , wherein the vector ensemble class includes one or more of: a center frequency, a bandwidth, a power, a signal to noise ratio, a signal to total noise and interference ratio, a modulation type, a type of signal, a location of the at least one signal of interest, an angle of arrival relative to a radio unit, an antenna index, an arrival rate, a time of arrival of the at least one signal of interest, a priority latency, an interaction vector including other signals with which the at least one signal of interest interacts, customer actionable data or information, a lower frequency component of the at least one signal of interest, an upper frequency component of the at least one signal of interest, and a time duration of the at least one signal of interest.
12. The system of claim 1 , wherein the wireless network resource optimization application creates a customer goals index vector.
13. The system of claim 1 , wherein the wireless network resource optimization application utilizes a constraint vector.
14. The system of claim 1 , wherein the wireless network resource optimization application creates the actionable data in real time or in near-real time.
15. The system of claim 1 , wherein the wireless network resource optimization application is operable to create the actionable data for one or more customers simultaneously using at least one vector.
16. The system of claim 1 , wherein the actionable data is used to generate at least one knowledge-based decision tree.
17. A system for dynamic spectrum utilization management in a radio frequency (RF) environment comprising:
at least one RF sensor operable to monitor the RF environment and to create RF data;
a Multi-Access Edge Computing (MEC) layer in a network slice or a subnetwork, wherein the MEC layer is in communication with a radio access network (RAN) and a core network; and
a wireless network resource optimization application in the MEC layer, wherein the wireless network resource optimization application includes at least one data analysis engine for analyzing the RF data;
wherein the at least one data analysis engine includes a detection engine and a learning engine, wherein the detection engine is operable to automatically detect at least one signal of interest, and wherein the learning engine is operable to learn the electromagnetic environment; and
wherein the wireless network resource optimization application is operable to use analyzed data from the at least one data analysis engine to create actionable data for optimizing network resources.
18. The system of claim 17 , wherein the network resources are optimized by reconfiguring the core network and/or the MEC associated with the network slice or the subnetwork.
19. The system of claim 17 , wherein the network resources are optimized by changing physical layer parameters of one or more customer devices and/or applications.
20. The system of claim 17 , wherein the at least one RF sensor is in communication with the MEC layer, wherein the at least one RF sensor is included in a base station and/or at least one spectrum monitoring unit, wherein the at least one spectrum monitoring unit includes a housing, at least one processor and memory, at least one receiver, and the at least one RF sensor.
21. The system of claim 17 , wherein the wireless network resource optimization application creates a vector ensemble class for the at least one signal of interest.
22. The system of claim 17 , wherein the wireless network resource optimization application utilizes a constraint vector.
23. A method for dynamic spectrum utilization management in an electromagnetic environment comprising:
providing a Multi-Access Edge Computing (MEC) layer in a network slice or a subnetwork and a wireless network resource optimization application in the MEC layer, wherein the MEC layer is in communication with a radio access network (RAN) and a core network, wherein the wireless network resource optimization application includes at least one data analysis engine for analyzing the measured data and a programmable rules and policy editor, wherein the programmable rules and policy editor includes at least one rule and/or at least one policy;
monitoring the electromagnetic environment using at least one monitoring sensor to create measured data;
analyzing the measured data using the at least one data analysis engine to create analyzed data, wherein the at least one data analysis engine includes a detection engine and a learning engine;
learning the electromagnetic environment using the learning engine;
automatically detecting at least one signal of interest using the detection engine;
the wireless network resource optimization application using analyzed data from the at least one data analysis engine to create actionable data; and
optimizing network resources using the actionable data.
24. The method of claim 23 , further including optimizing the network resources by reconfiguring the core network and/or the MEC associated with the network slice or the subnetwork.
25. The method of claim 23 , further including optimizing the network resources by changing physical layer parameters of one or more customer devices and/or applications.
26. The method of claim 23 , further including the wireless network resource optimization application creating a vector ensemble class for the at least one signal of interest including detected signal information.
27. The method of claim 23 , further including the wireless network resource optimization application utilizing a constraint vector.