Radio link quality prediction
System and techniques for radio link quality prediction are described herein. A mobile device may receive a device registration. Motion data for the mobile device may then be obtained. A predicted path for the mobile device may be derived from the motion data. A set of predicted radio metrics for the mobile device along the predicted path mat be produced via a dynamic coverage map. The set of predicted radio metrics may then be transmitted.
1. A device, comprising:
communication circuitry; and
processing circuitry to:
receive, via the communication circuitry, a link quality prediction (LQP) request from a requesting entity, wherein the LQP request is a request to predict a future quality of a radio link between a mobile device and a network;
predict, based on motion data for the mobile device and radio coverage data for the network, a future path of the mobile device and the future quality of the radio link along the future path, wherein the radio coverage data indicates estimated radio coverage across the network at different locations and times; and
send, via the communication circuitry, a link quality prediction (LQP) response to the requesting entity, wherein the LQP response includes one or more link quality predictions indicating the predicted future quality of the radio link between the mobile device and the network, wherein each link quality prediction includes:
a time at which a particular link quality prediction applies;
a type of metric predicted by the particular link quality prediction; and
a value for the type of metric predicted by the particular link quality prediction.
2. The device of claim 1 , wherein:
the requesting entity is the mobile device; or
the requesting entity is a service provider, wherein the mobile device is connected to the service provider via the network.
3. The device of claim 1 , wherein the LQP response includes one or more performance metrics indicating the predicted future quality of the radio link, wherein the one or more performance metrics include bandwidth or latency.
4. The device of claim 1 , wherein the LQP request is an LQP subscription request, wherein the LQP subscription request is a request to subscribe to changes in the predicted future quality of the radio link between the mobile device and the network.
5. The device of claim 1 , wherein the processing circuitry to predict, based on the motion data for the mobile device and the radio coverage data for the network, the future path of the mobile device and the future quality of the radio link along the future path is further to:
receive the motion data for the mobile device, wherein the motion data includes a geographic coordinate obtained from a satellite positioning service or a network location service; and
process the motion data using a trained classifier, wherein the trained classifier is trained to predict the future path of the mobile device based on the motion data.
6. The device of claim 1 , wherein the processing circuitry to predict, based on the motion data for the mobile device and the radio coverage data for the network, the future path of the mobile device and the future quality of the radio link along the future path is further to:
process the future path of the mobile device and the radio coverage data using a trained classifier, wherein the trained classifier is trained to predict the future quality of the radio link based on the future path of the mobile device and the radio coverage data.
7. The device of claim 1 , wherein the radio coverage data includes:
network infrastructure data, wherein the network infrastructure data indicates locations and load levels of network nodes in the network;
environment data associated with a physical environment in which the network nodes reside; and
user behavior data, wherein the user behavior data indicates usage patterns of users of the network.
8. The device of claim 1 , wherein the network is a cellular network, wherein the cellular network includes one or more base stations.
9. At least one non-transitory machine accessible storage medium having instructions stored thereon, wherein the instructions, when executed on processing circuitry, cause the processing circuitry to:
receive, via communication circuitry, a link quality prediction (LQP) request from a requesting entity, wherein the LQP request is a request to predict a future quality of a radio link between a mobile device and a network;
predict, based on motion data for the mobile device and radio coverage data for the network, a future path of the mobile device and the future quality of the radio link along the future path, wherein the radio coverage data indicates estimated radio coverage across the network at different locations and times; and
send, via the communication circuitry, a link quality prediction (LQP) response to the requesting entity, wherein the LQP response includes one or more link quality predictions indicating the predicted future quality of the radio link between the mobile device and the network, wherein each link quality prediction includes:
a time at which a particular link quality prediction applies;
a type of metric predicted by the particular link quality prediction; and
a value for the type of metric predicted by the particular link quality prediction.
10. The storage medium of claim 9 , wherein:
the requesting entity is the mobile device; or
the requesting entity is a service provider, wherein the mobile device is connected to the service provider via the network.
11. The storage medium of claim 10 , wherein the service provider is:
a content provider;
a video streaming service;
a video conferencing service;
a telephony service; or
a navigation service.
12. The storage medium of claim 9 , wherein the LQP response includes one or more performance metrics indicating the predicted future quality of the radio link, wherein the one or more performance metrics include bandwidth or latency.
13. The storage medium of claim 9 , wherein the LQP response includes one or more performance metrics indicating the predicted future quality of the radio link, wherein the one or more performance metrics include signal strength, transmission power, error rate, packet loss rate, or available link technology.
14. The storage medium of claim 9 , wherein each link quality prediction further indicates a probability of whether the particular link quality prediction is correct.
15. The storage medium of claim 9 , wherein the LQP response further includes a prediction count, wherein the prediction count indicates a number of link quality predictions included in the LQP response.
16. The storage medium of claim 9 , wherein the LQP request is an LQP subscription request, wherein the LQP subscription request is a request to subscribe to changes in the predicted future quality of the radio link between the mobile device and the network.
17. The storage medium of claim 9 , wherein the instructions that cause the processing circuitry to predict, based on the motion data for the mobile device and the radio coverage data for the network, the future path of the mobile device and the future quality of the radio link along the future path further cause the processing circuitry to:
receive the motion data for the mobile device, wherein the motion data includes a geographic coordinate obtained from a satellite positioning service or a network location service; and
process the motion data using a trained classifier, wherein the trained classifier is trained to predict the future path of the mobile device based on the motion data.
18. The storage medium of claim 9 , wherein the instructions that cause the processing circuitry to predict, based on the motion data for the mobile device and the radio coverage data for the network, the future path of the mobile device and the future quality of the radio link along the future path further cause the processing circuitry to:
process the future path of the mobile device and the radio coverage data using a trained classifier, wherein the trained classifier is trained to predict the future quality of the radio link based on the future path of the mobile device and the radio coverage data.
19. The storage medium of claim 9 , wherein the radio coverage data includes:
network infrastructure data, wherein the network infrastructure data indicates locations and load levels of network nodes in the network;
environment data associated with a physical environment in which the network nodes reside; and
user behavior data, wherein the user behavior data indicates usage patterns of users of the network.
20. The storage medium of claim 9 , wherein the network is a cellular network, wherein the cellular network includes one or more base stations.
21. A method, comprising:
receiving, via communication circuitry, a link quality prediction (LQP) request from a requesting entity, wherein the LQP request is a request to predict a future quality of a radio link between a mobile device and a network;
predicting, based on motion data for the mobile device and radio coverage data for the network, a future path of the mobile device and the future quality of the radio link along the future path, wherein the radio coverage data indicates estimated radio coverage across the network at different locations and times; and
sending, via the communication circuitry, a link quality prediction (LQP) response to the requesting entity, wherein the LQP response includes one or more link quality predictions indicating the predicted future quality of the radio link between the mobile device and the network, wherein each link quality prediction includes:
a time at which a particular link quality prediction applies;
a type of metric predicted by the particular link quality prediction; and
a value for the type of metric predicted by the particular link quality prediction.
22. The method of claim 21 , wherein the LQP response includes one or more performance metrics indicating the predicted future quality of the radio link, wherein the one or more performance metrics include bandwidth or latency.
23. The method of claim 21 , wherein the radio coverage data includes:
network infrastructure data, wherein the network infrastructure data indicates locations and load levels of network nodes in the network;
environment data associated with a physical environment in which the network nodes reside; and
user behavior data, wherein the user behavior data indicates usage patterns of users of the network.