Wireless Device Measurement Gap Pattern Transition

The patent applies parameter changes by dynamically adjusting measurement gap pattern parameters (such as gap length, periodicity, and time offset) based on triggering events. The UE transitions between PMGP and NMGP by modifying these parameters, allowing efficient measurement adaptation without complex transition control mechanisms.

The UE autonomously detects triggering events and performs self-service transitions between PMGP and NMGP without requiring complex network control. The device monitors conditions such as BWP changes and measurement requirements, then independently switches gap patterns, reducing transition control complexity while maintaining measurement efficiency.

The patent implements dynamics by enabling the UE to dynamically switch between PMGP and NMGP based on real-time triggering events. When fast measurement response is needed, the UE uses PMGP with pre-configured parameters. When scheduling flexibility is required, the UE transitions to NMGP. This dynamic adaptation resolves the contradiction between response time and flexibility.

The patent applies preliminary action through pre-configuration of measurement gap patterns. The network pre-configures PMGP parameters in advance, so when a triggering event occurs, the UE can immediately use the pre-prepared configuration without waiting for new configuration messages, thus reducing measurement response time while maintaining scheduling flexibility through on-demand transitions.

The patent extracts the transition trigger detection function from the network and places it in the UE. The UE independently monitors triggering events such as BWP changes and measurement requirements, then autonomously transitions between gap patterns. This extraction eliminates the need for frequent network signaling to control transitions, reducing signaling overhead while maintaining measurement adaptability.

The patent implements feedback mechanisms where the UE monitors system conditions (BWP status, measurement requirements) and provides implicit feedback through its autonomous transition decisions. The network configures triggering conditions in advance, and the UE responds to these conditions by selecting appropriate gap patterns, creating a feedback loop that achieves measurement adaptability without continuous network signaling.