A scene-based beam generation method for ground-to-air coverage based on convex polygon subdivision is provided and includes: obtaining a collection of base station positions by using a method of universal transverse mercator projection; constructing a three-dimensional (3D) low altitude signal coverage area; performing convex polygon subdivision on the area to be covered; and generating a beam configuration of each base station. The method realizes generation of beam configurations of base stations in the 3D low altitude signal coverage area, overcomes a problem that the existing 17 kind of scene-based beams cannot realize the coverage of 3D area, overcomes a problem of mismatch between network state information and beam configuration caused by dynamic adjustment of beam configurations. The beam configurations generated by the method does not need to obtain the number of users in real time to adjust the beam, and has a good coverage ability.

A scene-based beam generation method for ground-to-air coverage based on convex polygon subdivision is provided and includes: obtaining a collection of base station positions by using a method of universal transverse mercator projection; constructing a three-dimensional (3D) low altitude signal coverage area; performing convex polygon subdivision on the area to be covered; and generating a beam configuration of each base station. The method realizes generation of beam configurations of base stations in the 3D low altitude signal coverage area, overcomes a problem that the existing 17 kind of scene-based beams cannot realize the coverage of 3D area, overcomes a problem of mismatch between network state information and beam configuration caused by dynamic adjustment of beam configurations. The beam configurations generated by the method does not need to obtain the number of users in real time to adjust the beam, and has a good coverage ability.

Concepts and technologies disclosed herein are directed to computer vision-based dynamic radio frequency (“RF”) planning and optimization. According to one aspect disclosed herein, a system can monitor cell site data from a cell site. The system can determine that the cell site data represents a change to the cell site. In response to determining that the cell site data represents the change to the cell site, the system can update clutter data associated with the cell site to reflect the change. The system can determine a potential RF signal attenuation associated with the object. The system can then determine that the potential RF signal attenuation associated with the object meets or exceeds a threshold. The system can trigger a remedial action to mitigate the potential RF signal attenuation.

Concepts and technologies disclosed herein are directed to computer vision-based dynamic radio frequency (“RF”) planning and optimization. According to one aspect disclosed herein, a system can monitor cell site data from a cell site. The system can determine that the cell site data represents a change to the cell site. In response to determining that the cell site data represents the change to the cell site, the system can update clutter data associated with the cell site to reflect the change. The system can determine a potential RF signal attenuation associated with the object. The system can then determine that the potential RF signal attenuation associated with the object meets or exceeds a threshold. The system can trigger a remedial action to mitigate the potential RF signal attenuation.

Method and apparatus for scalable machine learning (ML)-based frameworks for resource planning and recommendations for Enterprise Networks are disclosed. In some embodiments, a method for determining network health assessment and providing network planning and recommendations in wireless enterprise networks is provided. The method quantifies resource health of a plurality of network elements operating within the enterprise network by calculating a plurality of distance metrics between acceptable health parameters and observed network resource utilization values associated and corresponding to each selected network element. The method ranks each of the network elements based upon the distance metrics calculated for each network element. Factors that negatively impact the resource health of the network elements are ranked in accordance to how severely they impact the performance of the network elements. The method and apparatus provide suggestions and recommendations to improve network performance of the network elements. An apparatus for scalable machine-learning (ML)-based frameworks for resource planning in enterprise networks is also disclosed.

Various arrangements for decreasing cellular network dead spots using microcells are detailed. A geographic map indicative of cellular network performance may be created. Using the geographic map, an area that has a cellular network dead spot can be identified. A subscriber database can be used to identify a subscriber address that is in a location to extend the cellular network within the dead spot. Based on analyzing the subscriber database to identify the subscriber address that is in the location to extend the cellular network, a microcell can be caused to be deployed at the subscriber address. Cellular services can then be provided using the microcell to various pieces of user equipment.

Various arrangements for decreasing cellular network dead spots using microcells are detailed. A geographic map indicative of cellular network performance may be created. Using the geographic map, an area that has a cellular network dead spot can be identified. A subscriber database can be used to identify a subscriber address that is in a location to extend the cellular network within the dead spot. Based on analyzing the subscriber database to identify the subscriber address that is in the location to extend the cellular network, a microcell can be caused to be deployed at the subscriber address. Cellular services can then be provided using the microcell to various pieces of user equipment.

The present disclosure relates to a 5th generation (5G) or pre-5G communication system for supporting a data transmission rate higher than that of a 4th generation (4G) communication system such as long term evolution (LTE). The present disclosure is to generate environment information for a network design, and a method for generating environment information may include determining a location difference value of a building between first information based on photographing and second information based on measurement, and correcting a location of an obstacle determined using the first information using the location difference value.

The present disclosure relates to a 5th generation (5G) or pre-5G communication system for supporting a data transmission rate higher than that of a 4th generation (4G) communication system such as long term evolution (LTE). The present disclosure is to generate environment information for a network design, and a method for generating environment information may include determining a location difference value of a building between first information based on photographing and second information based on measurement, and correcting a location of an obstacle determined using the first information using the location difference value.

Systems and methods model earth stations and other captive terrestrial sites as simulated cell sites in a radio access network (RAN) to identify potential cellular network interferers with the earth stations. A computing device selects an earth station within a geographic area of a RAN segment and model the earth station as a cell within the RAN segment, wherein the modeling creates a simulated earth station cell. The computing device obtains sector carrier data for cells in the RAN segment and scores, based on the sector carrier data, neighboring cells to the simulated earth station cell. The scoring indicates a level of potential interference of the neighboring cells with the earth station based on geo-spatial relevance. The computing device identifies projected mobility interference in neighboring cells to the earth station and provides prioritization recommendations for interference mitigation for the earth station based on the scoring and the identifying.