Proactive increase of bearer quality of service (QoS) in response to prediction that UE will experience reducted-throughput coverage while receiving streaming media

1. A method for proactively reconfiguring communication to a user equipment device (UE) in anticipation the UE experiencing a coverage-throughput reduction when the UE is receiving streaming media, the method comprising:

predicting, when the UE is receiving streaming media, that the UE is going to experience the coverage-throughput reduction, wherein predicting that the UE is going to experience the coverage-throughput reduction comprises predicting that the UE will transition from being served with first coverage having a first frequency bandwidth to being served instead with second coverage having a second frequency bandwidth narrower than the first frequency bandwidth; and

based at least in part on the predicting, proactively increasing a quality-of-service (QOS) level of a bearer through which the UE is receiving the streaming media, wherein the proactively increasing occurs before the UE experiences the coverage-throughput reduction so that the QoS level is increased by when the UE experiences the coverage-throughput reduction,

wherein proactively increasing the QoS level of the bearer through which the UE is receiving the streaming media comprises modifying a QoS parameter of the bearer to increase air-interface scheduling priority of the streaming media on the bearer such that a volume of data flowing on the bearer is increased.

2. The method of claim 1 , wherein predicting that the UE is going to experience the coverage-throughput reduction is based on the first coverage supporting up to a first throughput and the second coverage supporting up to just a second throughput that is lower than the first throughput.

3. The method of claim 1 , wherein the UE transitioning from being served with first coverage having a first frequency bandwidth to being served instead with second coverage having a second frequency bandwidth narrower than the first frequency bandwidth involves the UE transitioning from being served with dual-connectivity to being served instead with standalone connectivity.

4. The method of claim 3 , wherein the dual-connectivity is EUTRA-NR Dual Connectivity (EN-DC) in which the UE has concurrent connections on 4G Long Term Evolution (4G LTE) and 5G New Radio (5G NR), and wherein the standalone connectivity is standalone 4G LTE connectivity in which the UE has just a 4G LTE connection or standalone 5G NR connectivity in which the UE has just a 5G NR connection.

5. The method of claim 1 , wherein predicting, when the UE is receiving streaming media, that the UE is going to experience the coverage-throughput reduction comprises:

determining that the UE is engaged in a streaming media session in which the UE is receiving streaming media; and

determining that the UE is going to experience the coverage-throughput reduction.

6. The method of claim 1 , wherein proactively increasing the QoS level of the bearer through which the UE is receiving the streaming media comprises engaging in signaling to trigger a QoS modification of the bearer.

7. The method of claim 1 , wherein the bearer has a QoS Class Identifier (QCI) with a first associated QoS level, and wherein proactively increasing the QoS level of the bearer comprises changing the QCI of the bearer to a second QCI with a second associated QoS level higher than the first associated QoS level.

8. The method of claim 1 , wherein the increasing of the QoS level is temporary but lasts until at least after the UE has experienced the coverage-throughput reduction.

9. A computing system configured to proactively reconfigure communication to a user equipment device (UE) in anticipation the UE experiencing a coverage-throughput reduction when the UE is receiving streaming media, the computing system comprising:

at least one network communication interface; at least one processing unit;

at least one non-transitory data storage; and

program instructions stored in the at least one non-transitory data storage and executable by the at least one processing unit to carry out operations including:

predicting, when the UE is receiving streaming media, that the UE is going to experience the coverage-throughput reduction, wherein predicting that the UE is going to experience the coverage-throughput reduction comprises predicting that the UE will transition from being served with first coverage having a first frequency bandwidth to being served instead with second coverage having a second frequency bandwidth narrower than the first frequency bandwidth, and

based at least in part on the predicting, proactively increasing a quality-of-service (QOS) level of a bearer through which the UE is receiving the streaming media, wherein the proactively increasing occurs before the UE experiences the coverage-throughput reduction so that the QoS level is increased by when the UE experiences the coverage-throughput reduction,

wherein proactively increasing the QoS level of the bearer through which the UE is receiving the streaming media comprises modifying a QoS parameter of the bearer to increase air-interface scheduling priority of the streaming media on the bearer such that a volume of data flowing on the bearer is increased.

10. The computing system of claim 9 , wherein predicting that the UE is going to experience the coverage-throughput reduction is based on the first coverage supporting up to a first throughput and the second coverage supporting up to just a second throughput that is lower than the first throughput.

11. The computing system of claim 9 , wherein the UE transitioning from being served with first coverage having a first frequency bandwidth to being served instead with second coverage having a second frequency bandwidth narrower than the first frequency bandwidth involves the UE transitioning from being served with dual-connectivity to being served instead with standalone connectivity.

12. The computing system of claim 11 , wherein the dual-connectivity is EUTRA-NR Dual Connectivity (EN-DC) in which the UE has concurrent connections on 4G Long Term Evolution (4G LTE) and 5G New Radio (5G NR), and wherein the standalone connectivity is standalone 4G LTE connectivity in which the UE has just a 4G LTE connection or standalone 5G NR connectivity in which the UE has just a 5G NR connection.

13. The computing system of claim 9 , wherein predicting, when the UE is receiving streaming media, that the UE is going to experience the coverage-throughput reduction comprises:

determining that the UE is engaged in a streaming media session in which the UE is receiving streaming media; and

determining that the UE is going to experience the coverage-throughput reduction.

14. The computing system of claim 9 , wherein proactively increasing the QoS level of the bearer through which the UE is receiving the streaming media comprises engaging in signaling through a network communication interface, of the at least one network communication interface, to trigger a QoS modification of the bearer.

15. The computing system of claim 9 , wherein the bearer has a QoS Class Identifier (QCI) with a first associated QoS level, and wherein proactively increasing the QoS level of the bearer comprises changing the QCI of the bearer to a second QCI with a second associated QoS level higher than the first associated QoS level.

16. The computing system of claim 9 , wherein the increasing of the QoS level is temporary but lasts until at least after the UE has experienced the coverage-throughput reduction.

17. At least one non-transitory computer-readable medium embodying program instructions executable by at least one processing unit to carry out operations including:

predicting, when a user equipment device (UE) is receiving streaming media, that the UE is going to experience a coverage-throughput reduction, wherein predicting that the UE is going to experience the coverage-throughput reduction comprises predicting that the UE will transition from being served with first coverage having a first frequency bandwidth to being served instead with second coverage having a second frequency bandwidth narrower than the first frequency bandwidth; and

based at least in part on the predicting, proactively increasing a quality-of-service (QOS) level of a bearer through which the UE is receiving the streaming media, wherein the proactively increasing occurs before the UE experiences the coverage-throughput reduction so that the QoS level is increased by when the UE experiences the coverage-throughput reduction,

wherein proactively increasing the QoS level of the bearer through which the UE is receiving the streaming media comprises modifying a QoS parameter of the bearer to increase air-interface scheduling priority of the streaming media on the bearer such that a volume of data flowing on the bearer is increased.

18. The at least one non-transitory computer-readable medium of claim 17 , wherein predicting that the UE is going to experience the coverage-throughput reduction is based on the first coverage supporting up to a first throughput and the second coverage supporting up to just a second throughput that is lower than the first throughput.

19. The method of claim 3 , wherein the dual-connectivity is EUTRA-NR Dual Connectivity (EN-DC) in which the UE has concurrent connections on 4G Long Term Evolution (4G LTE) and 5G New Radio (5G NR), and wherein the standalone connectivity is standalone 5G NR connectivity in which the UE has just a 5G NR connection.

20. The computing system of claim 11 , wherein the dual-connectivity is EUTRA-NR Dual Connectivity (EN-DC) in which the UE has concurrent connections on 4G Long Term Evolution (4G LTE) and 5G New Radio (5G NR), and wherein the standalone connectivity is standalone 5G NR connectivity in which the UE has just a 5G NR connection.