Wireless Resource Scheduling Metric for QoS Guarantee
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Solution Overview
Problem
Existing wireless resource scheduling techniques in mobile communication systems fail to adequately consider the quantity of wireless resources allocatable to user terminals, particularly in heterogeneous networks and multi-cell environments, leading to inadequate Quality of Service (QoS) guarantees for high-priority traffic like VoIP and video services.
Innovation Solution
A method and apparatus that calculate a resource allocation metric reflecting the quantity of wireless resources available in the scheduling target cell, prioritizing traffic based on allocatable resources, using an equation that adjusts the priority of user terminals according to the available resource block groups and traffic load, ensuring efficient resource distribution and QoS for both macro and small cells, as well as carrier aggregation and licensed assisted access schemes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If existing wireless resource scheduling techniques are used, then general resource distribution is achieved, but QoS guarantees for high-priority traffic are insufficient
Solution Approach 1:
The scheduling metric is made dynamic by adjusting the weight α based on the quantity of allocatable wireless resources K. When resources are limited (K is small), the metric dynamically increases priority weighting to guarantee QoS for high-priority traffic. When resources are abundant, the metric reverts to proportional fairness for efficient resource distribution. This dynamic adaptation resolves the contradiction between QoS reliability and resource allocation efficiency.
Solution Approach 2:
The invention changes the parameter α in the scheduling metric according to the available resource quantity K. By modifying this key parameter based on system conditions, the scheduler transitions between different operational modes: QoS-guaranteed mode when resources are scarce, and efficiency-optimized mode when resources are plentiful. This parameter change strategy simultaneously addresses both QoS reliability and resource allocation efficiency.
2Reliability
If the quantity of wireless resources allocatable to user terminal is small, then QoS for high-priority traffic needs to be guaranteed, but resource allocation flexibility is reduced
Solution Approach 1:
The scheduling system dynamically adjusts the metric calculation based on the available resource quantity K. When K is small, the system adapts by increasing the weight of priority information in the metric, ensuring QoS guarantees. When K is large, the system adapts by reducing priority weight and emphasizing proportional fairness, maintaining scheduling flexibility. This dynamic behavior resolves the contradiction between QoS reliability and scheduling adaptability.
3Productivity
If multiple cells are operated on network for mobile communication, then network capacity is increased, but scheduling complexity increases
Solution Approach 1:
The invention provides a universal scheduling metric that works across multiple cells, carrier aggregation scenarios, and different resource allocation conditions. The same metric formula with adaptive parameter α handles diverse scenarios including macro cells, small cells, carrier aggregation, and licensed assisted access. This universal approach increases network capacity while avoiding the need for separate scheduling mechanisms for each scenario, thus managing complexity effectively.
Data Source
AI summary
Disclosed are a method and an apparatus that reflect the quantity of wireless resources allocatable to a user terminal in a scheduling target cell to calculate the quantity of available wireless resources for quality of service (QoS) requirements for each kind of varied traffic of user terminals and a metric having a flexible weight for the QoS requirements and support efficient wireless resource scheduling among the user terminals.