System, method, and apparatus for providing optimized network resources

A system for spectrum utilization management in a wireless network comprising:

• a Multi-Access Edge Computing (MEC) layer in a network slice;
• a wireless network resource optimization application in the MEC layer;
• a machine learning (ML) engine receiving detected signal information from a radio frequency (RF) environment;
• and
• a management and orchestration (MANO) module;
• wherein the MEC layer is in communication with at least one core network;
• wherein the wireless network resource optimization application analyzes detected signal information from a radio frequency (RF) environment;
• wherein the detected signal information includes a center frequency and/or bandwidth of at least one signal;
• wherein the wireless network resource optimization application is configured to analyze possible interactions based on the center frequency and/or the bandwidth of the at least one signal to create analyzed data;
• wherein the analyzed data is represented in a vector ensemble class for each signal in the electromagnetic environment;
• wherein the wireless network resource optimization application is configured to create a set by adding the possible interactions to the vector ensemble class;
• and
• wherein the wireless network resource optimization application is configured to create actionable data for optimizing network resources by combining the set with a customer goals index vector of binary values;
• 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 customer goals,
• wherein the wireless network resource optimization application is configured to optimize network resources based on the actionable data and a quality of service (QoS) required by at least one application;
• and
• wherein the MANO module is configured to coordinate data from the wireless network resource optimization application with the at least one core network to meet a customer network performance preference.

A method for spectrum utilization management in a wireless network comprising:

• a machine learning (ML) engine receiving detected signal information from at least one sensor in the electromagnetic environment;
• and
• a wireless network resource optimization application in a Multi-Access Edge Computing (MEC) layer analyzing the detected signal information;
• wherein the detected signal information includes a center frequency or bandwidth of at least one signal;
• the wireless network resource optimization application obtaining statistical information and analyzing possible interactions based on the center frequency or the bandwidth of the at least one signal to create analyzed data;
• wherein the analyzed data is represented in a vector ensemble class for each signal in the electromagnetic environment;
• the wireless network resource optimization application creating a set by adding the possible interactions to the vector ensemble class;
• and
• the wireless network resource optimization application creating actionable data for optimizing network resources by combining the set with a customer goals index vector of binary values;
• 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 customer goals,
• the wireless network resource optimization application optimizing network resources based on the actionable data;
• and
• a MANO module coordinating data from the wireless network resource optimization application with at least one core network to meet a customer network performance preference.