Method of controlling traffic in a cellular network and system thereof

1. A method of controlling traffic in a cellular network comprising a plurality of access points (APs) serving a plurality of user equipment devices (UEs), the method comprising: by a computerized system operatively connected to the plurality of APs and the plurality of UE devices,

continuously obtaining network data (NW data) related to at least part of APs from the plurality of APs;

continuously obtaining, from the UE devices, user equipment data (UE data) related to at least part of the UEs from the plurality of UEs;

aggregating the NW data and the UE data into statistical clusters, wherein

the NW data are aggregated into one or more NW statistical clusters using a first aggregation criterion and the UE data are separately aggregated into one or more UE statistical clusters using a second aggregation criterion different from the first aggregation criterion; or

the NW data and the UE data are aggregated into one or more combined statistical clusters, wherein UE data are aggregated with weights different from the weights of aggregating the NW data; and

continuously identifying at least one AP requiring corrective action by processing data informative of Network Key Performance Indicators (NW KPIs) and User Equipment Key Performance Indicators (UE KPIs), the data derived by processing the statistical clusters informative of NW data and UE data.

2. The method of claim 1 further comprising at least one of:

a. reporting the at least one identified AP requiring corrective actions to one or more predefined network entities;

b. identifying problems related to the at least one identified AP and alerting thereof to one or more predefined network entities;

c. identifying one or more desirable corrective actions with regard to the at least one identified AP; and

d. identifying desirable corrective actions with regard to the at least one identified AP and enabling thereof.

3. The method of claim 1 , wherein the processing comprises deriving one or more NW KPIs from the one or more NW statistical clusters, deriving one or more UE KPIs from the one or more UE statistical clusters, correlating between the one or more NW KPIs and the one or more UE KPIs and processing the correlated KPIs to identify the at least one AP requiring corrective action, wherein the correlating comprises identifying NW KPIs that correspond to APs involved in one or more services characterized by the one or more UE KPIs.

4. The method of claim 1 , further comprising enabling, with regard to the identified at least one AP, one or more corrective actions, wherein the one or more corrective actions improve one or more UE KPIs related to the identified at least one AP and keep deterioration of one or more NW KPIs related to the identified at least one AP as matching one or more predefined thresholds.

5. The method of claim 1 , wherein the second aggregation criterion is related to UEs located in one or more predefined geographical areas and/or UEs moving with a speed exceeding a predefined threshold.

6. The method of claim 3 , wherein the one or more NW KPIs and the one or more UE KPIs are indicative of different characteristics related to network performance.

7. The method of claim 3 , wherein the one or more NW KPIs are indicative of network performance parameters, and the one or more UE KPIs are indicative of number of UEs respectively suffered from insufficient network performance.

8. The method of claim 1 , wherein the processing comprises:

correlating between the one or more NW statistical clusters and the one or more UE statistical clusters, wherein the correlating is provided using, at least: data informative of network topology and/or UE data associated both with UE locations and APs serving the respective UEs, and/or UE data associated both with UE locations and APs neighboring APs serving the respective UEs;

deriving one or more NW KPIs from the one or more NW statistical clusters;

deriving one or more UE KPIs from the one or more UE statistical clusters;

generating one or more enhanced KPIs, wherein at least one enhanced KPI is configured as a single value representing a weighted combination of the one or more NW KPIs and one or more UE KPIs derived from respectively correlated statistical clusters; and

using the one or more enhanced KPIs to identify the at least one AP requiring corrective action.

9. The method of claim 8 , wherein a weight of the one or more UE KPIs in the at least one enhanced KPI depends on a use case related to desirable corrective actions, the use case selected from: uplink/downlink balancing, hotspots identification, LTE footprint optimization.

10. The method of claim 1 , wherein the processing comprises:

correlating between the one or more NW statistical clusters and the one or more UE statistical clusters, wherein the correlating is provided using, at least, data informative of network topology and/or UE data associated both with UE locations and APs serving the respective UEs;

deriving one or more NW KPIs from the NW statistical clusters; deriving one or more UE KPIs from the UE statistical clusters; and

generating one or more enhanced KPIs, wherein at least one enhanced KPI is configured as two values, one of the two values corresponding to the one or more NW KPIs and another of the two values, to respectively correlated one or more UE KPIs; and

using the one or more enhanced KPIs to identify the at least one AP requiring corrective action.

11. The method of claim 1 , wherein the processing comprises generating one or more enhanced KPIs informative of both NW KPIs and UE KPIs and configured as a single value derived from the combined statistical clusters; and using the one or more enhanced KPIs to identify the at least one AP requiring corrective action.

12. The method of claim 1 , wherein the weight of UE data when aggregated in the combined statistical clusters depends on a use case selected from: uplink/downlink balancing, hotspots identification, LTE footprint optimization.

13. A computerized system operatively connected to a plurality of APs operating in a cellular network and to a plurality of UE devices served by the plurality of APs, the computerized system comprising a computer configured to:

continuously obtain network data (NW data) related to at least part of APs from the plurality of APs;

continuously obtain, from the UE devices, user equipment data (UE data) related to at least part of the UEs from the plurality of UEs;

aggregate the NW data and the UE data into statistical clusters, wherein

the NW data are aggregated into one or more NW statistical clusters using a first aggregation criterion and the UE data are separately aggregated into one or more UE statistical clusters using a second aggregation criterion different from the first aggregation criterion; or

the NW data and the UE data are aggregated into one or more combined statistical clusters, wherein UE data are aggregated with weights different from the weights of aggregating the NW data; and

continuously identify at least one AP requiring corrective action by processing data informative of Network Key Performance Indicators (NW KPIs) and User Equipment Key Performance Indicators (UE KPIs), the data derived by processing the statistical clusters informative of NW data and UE data.

14. The computerized system of claim 13 , wherein the processing comprises deriving one or more NW KPIs from the one or more NW statistical clusters, deriving one or more UE KPIs from the one or more UE statistical clusters, correlating between the one or more NW KPIs and the one or more UE KPIs and processing the correlated KPIs to identify the at least one AP requiring corrective action, wherein the correlating comprises identifying NW KPIs that correspond to APs involved in one or more services characterized by the one or more UE KPIs.

15. The computerized system of claim 13 , further configured to enable, with regard to the identified at least one AP, one or more corrective actions, wherein the one or more corrective actions improve one or more UE KPIs related to the identified at least one AP and keep deterioration of one or more NW KPIs related to the identified at least one AP as matching one or more predefined thresholds.

16. The computerized system of claim 13 , wherein the processing comprises:

correlating between the one or more NW statistical clusters and the oneor more UE statistical clusters, wherein the correlating is provided using, at least: data informative of network topology and/or UE data associated both with UE locations and APs serving the respective UEs, and/or UE data associated both with UE locations and APs neighboring APs serving the respective UEs;

deriving one or more NW KPIs from the one or more NW statistical clusters;

deriving one or more UE KPIs from the one or more UE statistical clusters;

generating one or more enhanced KPIs, wherein at least one enhanced KPI is configured as a single value representing a weighted combination of the one or more NW KP Is and one or more UE KPIs derived from respectively correlated statistical clusters; and

using the one or more enhanced KPIs to identify the at least one AP requiring corrective action.

17. The computerized system of claim 13 , wherein the processing comprises:

correlating between the one or more NW statistical clusters and the one or more UE statistical clusters, wherein the correlating is provided using,

at least, data informative of network topology and/or UE data associated both with UE locations and APs serving the respective UEs;

deriving one or more NW KPIs from the NW statistical clusters;

deriving one or more UE KPIs from the UE statistical clusters; and

generating one or more enhanced KPIs, wherein at least one enhanced KPI is configured as two values, one of the two values corresponding to the one or more NW KPIs and another of the two values, to respectively correlated one or more UE KPIs; and

using the one or more enhanced KPIs to identify the at least one AP requiring corrective action.

18. The computerized system of claim 13 , wherein the processing comprises generating one or more enhanced KPIs informative of both NW KPIs and UE KPIs and configured as a single value derived from the combined statistical clusters; and using the one or more enhanced KPIs to identify the at least one AP requiring corrective action.

19. The computerized system of claim 13 , wherein the weight of UE data when aggregated in the combined statistical clusters depends on a use case selected from: uplink/downlink balancing, hotspots identification, LTE footprint optimization.

20. A non-transitory computer readable medium usable by a computerized system operatively connected to a plurality of APs operating in a cellular network and to a plurality of UE devices served by the plurality of APs, the computer readable medium comprising instructions that, when executed by a computer, cause the computer to perform operations comprising:

aggregating into statistical clusters continuously obtained network data (NW data) related to at least part of APs from the plurality of APs and continuously obtained, from the UE devices, user equipment data (UE data) related to at least part of the UEs from the plurality of UEs, wherein

the NW data are aggregated into one or more NW statistical clusters using a first aggregation criterion and the UE data are separately aggregated into one or more UE statistical clusters using a second aggregation criterion different from the first aggregation criterion; or

the NW data and the UE data are aggregated into one or more combined statistical clusters, wherein UE data are aggregated with weights different from the weights of aggregating the NW data; and

continuously identifying at least one AP requiring corrective action by processing data informative of Network Key Performance Indicators (NW KPIs) and User Equipment Key Performance Indicators (UE KPIs), the data derived by processing the statistical clusters informative of NW data and UE data.