Method and apparatus to generate wireless network areas of interest

1. A device, comprising:

a processing system including a processor; and

a memory that stores executable instructions that, when executed by the processing system, facilitate a performance of operations, the operations comprising:

obtaining data corresponding to a communication network;

applying a first algorithm to the data to generate a plurality of bins;

generating a respective score for each bin of the plurality of bins;

applying a second algorithm, based on the respective scores, to generate a plurality of clusters; and

generating a graph for each cluster of the plurality of clusters, wherein vertices of each graph are represented by the bins of the cluster, and wherein edges of each graph connect the bins of the cluster to adjacent bins of the cluster.

2. The device of claim 1 , wherein the first algorithm includes a data binning algorithm.

3. The device of claim 1 , wherein the second algorithm includes a one-dimensional k-means algorithm.

4. The device of claim 1 , wherein the operations further comprise:

applying a third algorithm to the graphs to generate a plurality of subgraphs.

5. The device of claim 4 , wherein the operations further comprise:

identifying, for each subgraph of the plurality of subgraphs, a number of vertices included in the subgraph,

allocating resources of the communication network based on the identifying of the number of vertices included in each subgraph.

6. The device of claim 1 , wherein the communication network supports video, gaming, Internet of Things (IoT) communications, or any combination thereof.

7. The device of claim 1 , wherein the communication network is one of a 5G mmWave network or a 6G network.

8. The device of claim 1 , wherein the operations further comprise:

weighting elements of the data and stack ranking the bins to generate the scores.

9. The device of claim 1 , wherein the obtaining of the data comprises obtaining first data from a plurality of handsets.

10. The device of claim 9 , wherein the obtaining of the data comprises obtaining second data corresponding to census population data, building data, road data, city-based data, town-based data, village-based data, or any combination thereof.

11. The device of claim 1 , wherein the data is associated with a first metric included in a plurality of metrics, wherein the plurality of metrics is associated with the communication network, and wherein the operations further comprise:

obtaining a selection of the first metric; and

filtering second data based on the obtaining of the selection to obtain the data, wherein the second data is associated with the plurality of metrics.

12. The device of claim 11 , wherein the plurality of metrics comprises: a signal strength, interference, noise, or any combination thereof.

13. The device of claim 11 , wherein the plurality of metrics comprises a coverage of a first portion of the communication network.

14. The device of claim 11 , wherein the plurality of metrics comprises a first capacity of a first cell of the communication network and a second capacity of a second cell of the communication network.

15. The device of claim 14 , wherein the operations further comprise:

redirecting communication traffic associated with the first cell to the second cell based on the first capacity and the second capacity.

16. The device of claim 15 , wherein the plurality of metrics comprises a first load of the first cell and a second load of the second cell, and wherein the redirecting of the communication traffic is further based on the first load and the second load.

17. A non-transitory machine-readable medium, comprising executable instructions that, when executed by a processing system including a processor, facilitate a performance of operations, the operations comprising:

applying a first algorithm to first data to generate a plurality of bins;

applying a second algorithm, based on respective scores associated with each of the plurality of bins, to generate a plurality of clusters;

generating a graph for each cluster of the plurality of clusters, wherein vertices of each graph are represented by the bins of the cluster, and wherein edges of each graph connect the bins of the cluster to adjacent bins of the cluster; and

allocating resources of a communication network based on the generating of the graph for each cluster of the plurality of clusters.

18. The non-transitory machine-readable medium of claim 17 , wherein the first algorithm comprises a data binning algorithm and the second algorithm comprises a k-means clustering algorithm.

19. A method, comprising:

obtaining, by a processing system including a processor, first data based on filtering second data in accordance with a selection of at least one metric included in a plurality of metrics, the plurality of metrics associated with a communication network;

applying, by the processing system, a data binning algorithm to the first data to generate a plurality of bins;

applying, by the processing system, a one-dimensional k-means algorithm to scores associated with the plurality of bins to generate a plurality of clusters;

generating, by the processing system, at least one graph for the plurality of clusters; and

identifying, by the processing system, at least one parameter associated with the communication network to modify based on an analysis of: the at least one graph, at least one subgraph associated with the at least one graph, or a combination thereof.

20. The method of claim 19 , wherein the at least one parameter comprises: a transmission power, a receiver sensitivity, a frequency or frequency band of a communication supported by the communication network, a radio access technology utilized by a communication device of the communication network, or any combination thereof, the method further comprising:

modifying, by the processing system and based on the identifying, the at least one parameter.