Method and system to predict network performance of a fixed wireless network

1. A method performed by an electronic device to predict network performance of a fixed wireless network, the method comprising:

receiving data of the fixed wireless network, the data including one or more of weather condition samples, man-made structure data sample, or geographic data samples;

modeling the data using a plurality of functions, the modeling comprises:

identifying a prediction function that provides a best approximation of the data based on a user preference of approximation speed and accuracy;

predicting a network performance value in a future time using the prediction function, the network performance value being a value for signal strength; and

notifying when the predicted network performance value fails to meet a threshold value.

2. The method of claim 1 , wherein the data comprises data from a single geographic area or from a single time duration.

3. The method of claim 1 , wherein identifying the prediction function that provides the best approximation of the data comprises:

providing the data to an offline computing system;

approximating the data using the plurality of functions simultaneously; and

identifying the prediction function using an accuracy measure of the approximation of the plurality of functions based on the user preference.

4. The method of claim 1 , wherein the plurality of functions comprises:

a function determining a moving average of the data;

a function determining a weighted moving average of the data;

a function determining a trend of the data using exponential smoothing;

a function determining seasonality of the data using Holt Winters filtering; and

a function determining a seasonality of the data based on lagging data values.

5. The method of claim 1 , wherein the data comprises a same type of data as that of the network performance value.

6. The method of claim 1 , wherein the data comprises a plurality of types of data to predict the network performance value.

7. The method of claim 6 , wherein the plurality of functions comprises:

a multi-variate linear regression (MLR) function, wherein each type of the data is a variable of the MLR function; and

an autoregressive integrated moving average function with an external factor (ARIMAX), wherein each type of the data is a variable of the ARIMAX function.

8. The method of claim 1 , wherein the notifying comprises using a Representational state transfer (REST) application programming interface (API).

9. The method of claim 1 , wherein the user preference of approximation speed and accuracy is provided through a Representational state transfer (REST) application programming interface (API).

10. An electronic device to be deployed in a fixed wireless network, comprising:

a processor and computer-readable storage medium that provides instructions that, when executed by the processor, cause the electronic device to perform:

receiving data of the fixed wireless network, the data including one or more of weather condition samples, man-made structure data sample, or geographic data samples;

modeling the data using a plurality of functions, the modeling comprises: identifying a prediction function that provides a best approximation of the data based on a user preference of approximation speed and accuracy;

predicting a network performance value in a future time using the prediction function, the network performance value being a value for signal strength; and

notifying when the predicted network performance value fails to meet a threshold value.

11. The electronic device of claim 10 , wherein the identification of the prediction function is to perform:

providing the data to an offline computing system;

approximating the data using the plurality of functions simultaneously; and

identifying the prediction function using an accuracy measure of the approximation of the plurality of functions based on the user preference.

12. The electronic device of claim 10 , wherein the data comprises a plurality of types of data that are distinct from that of the network performance value.

13. A non-transitory computer-readable storage medium that provides instructions that, when executed by a processor of an electronic device, cause the electronic device to perform:

receiving data of a fixed wireless network, the data including one or more of weather condition samples, man-made structure data sample, or geographic data samples;

modeling the data using a plurality of functions, the modeling comprises: identifying a prediction function that provides a best approximation of the data based on a user preference of approximation speed and accuracy;

predicting a network performance value in a future time using the prediction function, the network performance value being a value for signal strength; and

notifying when the predicted network performance value fails to meet a threshold value.

14. The non-transitory computer-readable storage medium of claim 13 , where the plurality of functions comprises:

a function determining a moving average of the data;

a function determining a weighted moving average of the data;

a function determining a trend of the data using exponential smoothing;

a function determining seasonality of the data using Holt Winters filtering; and

a function determining a seasonality of the data based on lagging data values.

15. The non-transitory computer-readable storage medium of claim 13 , wherein the user preference of approximation speed and accuracy is provided through a Representational state transfer (REST) application programming interface (API).