Abstract: A method and system for blindly triggering handover based on past failures to trigger handover of beamforming-served devices. A computing system identifies a geolocation area where wireless communication devices (WCDs) that are served with beamforming by a first access node tend to experience radio link failure after having reported to the first access node being within threshold weak coverage of the first access node and threshold strong coverage of a second access node. And, based on the identifying, the computing system then blindly triggers handover of a given WCD from the first access node to the second access node in response to determining that the given WCD is served with beamforming by the first access node while positioned in the identified geolocation area.

Abstract: A timeout period for a base station to wait for a UE's response to bearer-setup messaging from the base station will be set based on an evaluation of how often the UE (or a class of UEs of which the UE is a member) has experienced bearer-setup failures. For instance, the base station could generally apply a default timeout period for waiting to receive bearer-setup response messaging from UEs. But for a given UE that has recently experienced a high rate of bearer-setup failures, the base station could apply a longer timeout period, to help cope with that UE's tendency to be slower to respond to the base station's bearer-setup messaging.

Abstract: When a network entity receives packets transmitted from a user equipment device (UE), the network entity will detect that a threshold number of those packets exceed the network entity's maximum transmission unit (MTU), and the network entity will responsively cause the UE to reduce the UE's MTU. In particular, the network entity will responsively transmit to the UE, within a header of a packet carrying bearer data to the UE, a directive for the UE to decrease the UE's MTU.

Abstract: A method comprises a client executing on a processor of a UE, where the client is monitoring an application log and communication log for a plurality of user applications and communication applications. The client measures a volume of transactions and a set of performance metrics associated with UE resource usage. The client generates a custom device profile that establishes baselines for each of the plurality of user applications and identifies any deviations from the baselines. The client creates a bounded threshold based on the deviations, and detects that at least one of the plurality of user applications has exceeded the bounded threshold. The client determines that the bounded threshold was exceeded based on an application trigger and a network trigger, and in response, initiates a response action. The client also captures the communication log, the application log and application cache corresponding to the user application.

Abstract: When a network entity receives packets transmitted from a user equipment device (UE), the network entity will detect that a threshold number of those packets exceed the network entity's maximum transmission unit (MTU), and the network entity will responsively cause the UE to reduce the UE's MTU. In particular, the network entity will responsively transmit to the UE, within a header of a packet carrying bearer data to the UE, a directive for the UE to decrease the UE's MTU.

Abstract: A method of wireless communication.

Abstract: A method of wireless communication.

Abstract: A method and system is disclosed for controlling communication behavior of application programs running on a user equipment device (UE) based on joint consideration of predicted roaming and predicted communication behavior of the application programs. A UE may monitor its operational state data during times when it is operating in a wireless network of a home service provider and during other times when it is roaming in a wireless network of a different service provider, and apply the monitored operational state data to a roaming prediction model configured for predicting future roaming state. The UE may also monitor communication behavior data of resident application programs, and apply the monitored communication behavior data to an application-communication prediction model configured for predicting future communication behavior of the applications.