UE Stationary Mode Detection with Two-Stage Transition Verification
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional stationary mode detection mechanisms in smartphones and user equipment (UE) are prone to false transitions due to signal fluctuations in noisy or dynamic wireless environments, leading to reduced power saving gains and increased battery consumption.
Innovation Solution
Implementing a two-stage detection process involving one-shot and sequential detection to confirm stationary mode conditions, with the introduction of an additional 'deep stationary mode' to stabilize power savings in varying environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional one-shot detection mechanism is used to detect stationary mode conditions, then the detection process is simple and quick, but false transitions occur due to signal fluctuations leading to reduced power saving gains
Solution Approach 1:
The detection mechanism is divided into two independent stages: one-shot detection and sequential detection. The one-shot detection quickly checks initial stationary mode conditions, while the sequential detection verifies these conditions over multiple measurement occasions. This segmentation allows the system to maintain high reliability through verification while keeping the initial detection simple and quick.
Solution Approach 2:
The one-shot detection performs a preliminary check of stationary mode conditions before committing to a mode transition. This preliminary action filters out obvious non-stationary cases quickly, and only proceeds to the more complex sequential detection when the preliminary check suggests stationary conditions, thus maintaining efficiency while improving reliability.
2Reliability
If sequential detection with multiple verification stages is implemented, then false transitions are reduced improving power saving stability, but the detection process becomes more complex and time-consuming
Solution Approach 1:
The sequential detection is segmented into multiple measurement occasions rather than requiring all measurements to complete before decision. The system can make intermediate assessments and adjust detection intensity based on accumulating evidence, reducing overall detection time while maintaining stability through multiple verification points.
Solution Approach 2:
The system performs partial sequential detection by evaluating conditions after a subset of measurement occasions rather than requiring all measurements to complete. When sufficient evidence accumulates to confidently determine stationary mode, the detection process can conclude early, avoiding unnecessary time consumption while maintaining reliability through the partial verification already performed.
3Adaptability or versatility
If the UE frequently transitions between stationary and non-stationary modes due to false detection, then the system remains responsive to environmental changes, but power consumption increases and battery life decreases
Solution Approach 1:
The sequential detection mechanism provides feedback verification before confirming mode transitions. By requiring multiple measurement occasions to verify stationary conditions before transitioning to power-saving mode, the system reduces false positives that would cause unnecessary mode switches. This feedback loop maintains adaptability to genuine environmental changes while filtering out transient fluctuations that would otherwise trigger wasteful transitions.
Data Source
AI summary
A method includes performing, at a user equipment (UE), a one-shot detection during a first time period to detect whether a first set of stationary mode conditions are satisfied to transition from a first stationary mode to a second stationary mode. Responsive to the one-shot detection, the method further includes executing a sequential detection during a second time period after the first time period to confirm whether to switch to the second stationary mode.