Optimization of mobile phone service during power failure

1. A computer-implemented method for optimizing mobile telecommunications service, comprising:

identifying one or more of a plurality of base stations to which non-emergency electrical power has been interrupted;

determining an initial number of users in areas corresponding to the one or more of the plurality of base stations;

scheduling an initial battery power operation for the plurality of base stations;

generating a user location probability model and a user call probability model;

monitoring user calls and user movement after the battery power operation has started;

updating the user location probability model and the user call probability model based on the monitoring; and

updating the battery power operation scheduling for the plurality of base stations based on at least one of a current number of users, the updated user location probability model and the updated user call probability model.

2. The method as recited in claim 1 , wherein the scheduling includes scheduling the initial battery power operation based on at least one of the initial number of users, the user location probability model, and the user call probability model.

3. The method as recited in claim 1 , further comprising updating battery power operation scheduling for the plurality of base stations, wherein the updated battery power operation scheduling includes updating the battery power operation scheduling to minimize average wait time for a call connection.

4. The method as recited in claim 1 , further comprising updating battery power operation scheduling for the plurality of base stations, wherein the updated battery power operation scheduling includes updating the battery power operation scheduling to maximize duration of battery power driven operation of the plurality of base stations.

5. The method as recited in claim 1 , further comprising updating battery power operation scheduling for the plurality of base stations, wherein the steps of the monitoring of user calls and user movement, the updating the user location probability model and the user call probability, and the updating the battery power operation scheduling for the plurality of base stations are repeated until optimization has been achieved.

6. The method as recited in claim 1 , further comprising scheduling initial battery power operation for the plurality of base stations, wherein the scheduling includes scheduling initial battery power operation based on the initial number of users, the user location probability model, and the user call probability model.

7. A non-transitory computer readable storage medium comprising a computer readable program for optimizing mobile telecommunications service, wherein the computer readable program when executed on a computer causes the computer to perform the steps of:

identifying one or more of a plurality of base stations to which non-emergency electrical power has been interrupted;

calculating an initial number of users in areas corresponding to the one or more of the plurality of base stations;

scheduling an initial battery power operation for the plurality of base stations;

generating a user location probability model and a user call probability model;

monitoring user calls and user movement after the battery power operation has started;

updating the user location probability model and the user call probability model based on the monitoring; and

updating the battery power operation scheduling for the plurality of base stations based on at least one of a current number of users, the updated user location probability model and the updated user call probability model.

8. The non-transitory computer readable storage medium comprising a computer readable program as recited in claim 7 , wherein the scheduling includes scheduling the initial battery power operation based on at least one of the initial number of users, the user location probability model, and the user call probability model.

9. The non-transitory computer readable storage medium comprising a computer readable program as recited in claim 7 , further comprising updating battery power operation scheduling for the plurality of base stations, wherein the updated battery power operation scheduling includes updating the battery power operation scheduling to minimize average wait time for a call connection.

10. The non-transitory computer readable storage medium comprising a computer readable program as recited in claim 7 , further comprising updating battery power operation scheduling for the plurality of base stations, wherein the updated battery power operation scheduling includes updating the battery power operation scheduling to maximize duration of battery power driven operation of the plurality of base stations.

11. The non-transitory computer readable storage medium comprising a computer readable program as recited in claim 7 , further comprising updating battery power operation scheduling for the plurality of base stations, wherein the steps of the monitoring of user calls and user movement, the updating the user location probability model and the user call probability, and the updating the battery power operation scheduling for the plurality of base stations are repeated until optimization has been achieved.

12. A system for optimizing mobile telecommunications service, comprising:

an identification module configured to identify one or more of a plurality of base stations to which non-emergency electrical power has been interrupted;

a user location prediction module configured to calculate an initial number of users in areas corresponding to the one or more of the plurality of base stations;

a battery scheduling module configured to schedule an initial battery power operation for the plurality of base stations;

one or more prediction modules configured to generate a user location probability model and a user call probability model;

a monitoring module configured to monitor user calls and user movement after the battery power operation has started; and

one or more updating modules configured to update the user location probability model and the user call probability model based on the monitoring;

wherein the battery scheduling updating module configured to update the battery power operation scheduling for the plurality of base stations based on at least one of a current number of users, the updated user location probability model and the updated user call probability model.

13. The system as recited in claim 12 , wherein the scheduling the initial battery power operation is based on at least one of the initial number of users, the user location probability model, and the user call probability model.

14. The system as recited in claim 12 , further comprising a battery scheduling updating module configured to update battery power operation scheduling for the plurality of base stations, wherein the updated battery power operation scheduling minimizes average wait time for a call connection.

15. The system as recited in claim 12 , further comprising a battery scheduling updating module configured to update battery power operation scheduling for the plurality of base stations, wherein the updated battery power operation scheduling maximizes duration of battery power driven operation of the plurality of base stations.

16. The system as recited in claim 12 , further comprising a battery scheduling updating module configured to update battery power operation scheduling for the plurality of base stations, wherein the steps of the monitoring of user calls and user movement, the updating the user location probability model and the user call probability, and the updating the battery power operation scheduling for the plurality of base stations are repeated until optimization has been achieved.

17. The system as recited in claim 12 , further comprising a battery scheduling module configured to schedule initial battery power operation for the plurality of base stations, wherein the scheduling initial battery power operation is based on the initial number of users, the user location probability model, and the user call probability model.