User Equipment Scheduling Assistance for Wireless Latency Reduction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing wireless communication systems face challenges in optimizing scheduling decisions due to lack of accurate real-time traffic pattern information, leading to inefficiencies in power usage and latency.
Innovation Solution
A method where user equipment (UE) receives scheduling assistance requests from a base station, generates and transmits scheduling assistance information based on application layer traffic patterns, enabling better scheduling accuracy and power savings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If scheduling decisions are made without real-time traffic pattern information, then system complexity is reduced, but scheduling accuracy and efficiency deteriorate
Solution Approach 1:
The patent introduces an intermediary mechanism where the UE generates scheduling assistance information based on application layer traffic patterns and provides it to the base station. This intermediary information layer enables accurate scheduling decisions without requiring the base station to directly monitor and process all application layer traffic data, thus improving scheduling accuracy while limiting the increase in system complexity.
Solution Approach 2:
The UE performs self-service by autonomously generating scheduling assistance information from its own application layer traffic patterns. This allows the UE to serve its own scheduling needs accurately without burdening the base station with complex real-time traffic analysis, resolving the contradiction between scheduling accuracy and system complexity.
2Measurement precision
If real-time traffic information is collected and processed, then scheduling accuracy improves, but power consumption increases
Solution Approach 1:
The patent extracts only the essential scheduling assistance information from application layer traffic patterns that is needed for accurate scheduling, rather than collecting and processing all raw traffic data. This selective extraction approach enables improved scheduling accuracy while minimizing the power consumption associated with data collection and processing.
Solution Approach 2:
The UE performs partial action by generating only the specific scheduling assistance information required for scheduling decisions, rather than fully processing all application layer traffic patterns. This partial processing approach achieves sufficient scheduling accuracy while reducing power consumption compared to complete traffic pattern analysis.
3Productivity
If scheduling assistance information is transmitted frequently, then scheduling efficiency improves, but latency increases
Solution Approach 1:
The patent employs parameter changes by dynamically adjusting the frequency and timing of scheduling assistance information transmission based on traffic pattern variations. When traffic patterns are stable, transmission frequency is reduced to minimize latency. When traffic patterns change significantly, transmission frequency increases to maintain scheduling efficiency, thus resolving the contradiction between scheduling efficiency and latency.
Data Source
AI summary
Provided is a method for a user equipment (UE), comprising: receiving request for scheduling assistance from a base station, wherein the request for scheduling assistance comprises scheduling configuration to be applied to a set of flows of a scheduled terminal on an application layer; informing the scheduled terminal of the scheduling configuration; receiving scheduling assistance information from the scheduled terminal, wherein the scheduling assistance information is generated by the scheduled terminal based on the set of flows of the scheduled terminal on the application layer; and transmitting the scheduling assistance information to the base station.