System, method, and apparatus for providing dynamic, prioritized spectrum management and utilization
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.
1. A system for intermodulation distortion analysis and mitigation in an electromagnetic environment comprising:
at least one monitoring sensor including at least one receiver channel operable to monitor and capture electromagnetic environment data and create measured data based on the electromagnetic environment; and
at least one data analysis engine operable to create at least one utilization mask based on the measured data;
wherein the at least one data analysis engine is operable to select at least one parameter based on the measured data and customer goals and/or a service provided to at least one user equipment (UE) device and store the at least one parameter in a parameter block;
wherein the at least one data analysis engine is configured to analyze the at least one utilization mask to identify at least one signal and intermodulation, thereby creating analyzed data;
wherein the at least one data analysis engine is operable to identify and/or sort intermodulation distortion (IMD) components of the at least one signal; and
wherein the at least one data analysis engine is operable to apply artificial intelligence (AI) and/or machine learning (ML) to the analyzed data and the at least one parameter to determine the IMD components.
2. The system of claim 1 , wherein the customer goals are included in a customer goals index vector.
3. The system of claim 2 , wherein the customer goals index vector is a binary vector.
4. The system of claim 1 , wherein the at least one parameter is selected based on a type of the identified signal and/or applications and engines in operation within the system.
5. The system of claim 1 , wherein the at least one data analysis engine is operable to detect at least one wideband signal and/or at least one narrowband signal.
6. The system of claim 1 , wherein the at least one data analysis engine is operable to provide a recommendation for at least one parameter of the at least one signal based on the analyzed data.
7. The system of claim 6 , wherein the system is operable to identify an adjustment of the at least one parameter of the at least one signal.
8. The system of claim 7 , wherein the at least one parameter is a power level of the at least one signal.
9. The system of claim 1 , further comprising a noise floor estimator operable to estimate a bin-wise noise model, estimate a bin-wise noise plus signal model, determine a bin-level probability of false alarm, determine a bin-level threshold, determine a channel-level probability of false alarm, determine a channel-level level threshold, calculate a detection vector, count a number of elements above the bin-level threshold, determine a probability of false alarm, determine a probability of missed detection, and/or determine an overall detection probability.
10. The system of claim 1 , further comprising a blind detection engine operable to estimate a number of channels, corresponding bandwidths for the number of channels, and/or center frequencies using an averaged power spectral density (PSD) of the at least one signal.
11. The system of claim 1 , wherein the at least one data analysis engine includes an intermodulation analysis workflow.
12. The system of claim 11 , wherein the intermodulation analysis workflow includes a narrowband sorting block, a wideband sorting block, and/or an intermodulation calculator.
13. The system of claim 12 , wherein the narrowband sorting block is operable to sort narrowband signals by a dynamically adjustable threshold based on the customer goals.
14. A system for intermodulation distortion analysis and mitigation in an electromagnetic environment comprising:
at least one monitoring sensor operable to monitor and capture electromagnetic environment data and create measured data based on the electromagnetic environment;
at least one data analysis engine operable to create at least one utilization mask based on the measured data; and
at least one mitigation subsystem in communication with the at least one data analysis engine;
wherein the at least one data analysis engine is operable to identify at least one signal;
wherein the at least one data analysis engine is operable to select at least one parameter based on measured data and customer goals and/or a service provided to at least one user equipment (UE) device and store the at least one parameter in a parameter block;
wherein the at least one data analysis engine is configured to analyze the at least one utilization mask and/or the at least one parameter to identify at least one signal and intermodulation distortion (IMD), thereby creating analyzed data; and
wherein the at least one mitigation subsystem is operable to provide at least one report of detected IMD components and/or perform IMD set optimization based on the analyzed data and the customer goals.
15. The system of claim 14 , wherein the at least one mitigation subsystem is operable to optimize detected IMD further based on the service provided to at the least one user equipment (UE) device.
16. The system of claim 14 , wherein the at least one parameter is selected based on a type of the identified signal and/or applications and engines in operation within the system.
17. A method for intermodulation distortion analysis and mitigation in an electromagnetic environment comprising:
at least one sensor creating measured data based on the electromagnetic environment;
at least one data analysis engine creating at least one utilization mask based on the measured data;
the at least one data analysis engine analyzing the at least one utilization mask to identify at least one signal and intermodulation distortion (IMD) to create analyzed data;
the at least one data analysis engine selecting at least one parameter based on the measured data and a type of the identified signal, applications and engines in operation within the system, customer goals, and/or a service provided to at least one user equipment (UE) device;
the at least one data analysis engine storing the at least one parameter in a parameter block; and
the at least one data analysis engine performing intermodulation distortion mitigation using the analyzed data and the at least one parameter.
18. The method of claim 17 , wherein the customer goals are included in a binary customer goals index vector.
19. The method of claim 17 , further comprising the at least one data analysis engine providing mitigation recommendations for at least one parameter of the at least one signal based on the analyzed data.
20. The method of claim 17 , further comprising the at least one data analysis engine analyzing intermodulation using a sorting block and intermodulation calculator.