Multi-AP Resource Scheduling With Predictive Feedback Allocation
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Solution Overview
Problem
In multi-AP wireless networks, uncoordinated air interface resource contention leads to resource waste and low utilization due to conflicts among access points, which is exacerbated as network density increases.
Innovation Solution
A hybrid scheduling framework where a control device centrally manages resource allocation and APs distribute it, using predicted and actual data transmission performance to adjust time-frequency resources dynamically, ensuring terminals meet resource allocation objectives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If multiple APs operate independently without coordination, then each AP can autonomously manage its resources, but air interface resource contention increases and resource utilization decreases
Solution Approach 1:
The patent introduces a coordination mechanism as an intermediary between multiple APs. This coordinator manages resource allocation across APs, reducing uncoordinated contention while maintaining autonomous operation capabilities. The intermediary resolves conflicts and optimizes resource distribution without requiring complete centralization.
2Force
If predicted data transmission performance is used for resource allocation, then resource allocation can be performed in advance, but actual data transmission performance may differ from predicted performance
Solution Approach 1:
The patent implements a feedback mechanism where actual data transmission performance is measured and used to adjust resource allocation decisions. The system compares predicted performance with actual performance and refines future predictions based on the discrepancy, improving measurement precision over time while maintaining proactive resource allocation.
3Manufacturing precision
If time-frequency resources are reallocated based on actual data transmission performance, then resource allocation accuracy improves, but scheduling complexity increases
Solution Approach 1:
The patent implements dynamic resource allocation where the scheduling system adapts its complexity based on actual performance variations. When performance is stable, simpler allocation schemes are used; when variations are detected, the system dynamically adjusts resource allocation with increased sophistication, optimizing the balance between accuracy and complexity.
Data Source
AI summary
Disclosed is a resource allocation method. The method includes: obtaining first scheduling information based on predicted data transmission performance and a resource allocation objective of a plurality of terminals; sending a resource allocation indication to a plurality of APs based on the first scheduling information; obtaining actual data transmission performance that is of the plurality of terminals and that is sent by the plurality of APs, where the actual data transmission performance is data transmission performance of the plurality of terminals upon resource allocation performed on the plurality of terminals based on the resource allocation indication; obtaining second scheduling information based on the actual data transmission performance and the resource allocation objective; and sending the resource allocation indication to the plurality of APs based on the second scheduling information.