Hybrid AP Scheduling for Multi-AP Wireless Resource Allocation
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Solution Overview
Problem
In multi-AP wireless networks, uncoordinated resource contention leads to inefficient utilization of air interface resources due to conflicts, resulting in resource waste and reduced network performance.
Innovation Solution
A hybrid scheduling framework that utilizes a control device for centralized coordination and APs for distributed resource allocation, adjusting time-frequency resources based on predicted and actual data transmission performance to optimize network objectives such as throughput and latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If multiple APs contend for air interface resources in an uncoordinated manner, then each AP can independently manage its own resources, but wireless resource utilization decreases due to conflicts and avoidance phases
Solution Approach 1:
The patent segments the resource allocation task into two parts: centralized scheduling decisions made by the controller based on predicted performance, and distributed execution by APs. This segmentation allows APs to maintain operational independence while the controller coordinates resource allocation to avoid conflicts and improve utilization.
Solution Approach 2:
The patent implements a feedback mechanism where actual data transmission performance is measured and fed back to the controller. The controller uses this feedback to adjust future scheduling decisions, creating a closed-loop system that continuously optimizes resource allocation based on real-world performance rather than predictions alone.
2Productivity
If predicted data transmission performance is used for resource allocation, then scheduling decisions can be made proactively, but actual performance may differ from predictions causing allocation suboptimality
Solution Approach 1:
The patent performs preliminary resource allocation based on predicted data transmission performance, allowing the system to make proactive scheduling decisions before actual transmission occurs. This enables the system to optimize resource distribution in advance rather than reacting to actual performance after the fact.
Solution Approach 2:
The patent measures actual data transmission performance and feeds this information back to the controller, which then uses the feedback to refine future predictions and adjustments. This feedback loop compensates for any inaccuracies in initial predictions by adapting to actual conditions.
Data Source
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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. In this application, a hybrid scheduling framework controlled by a control device in a centralized manner and coordinated by the AP in a distributed manner is used. The control device may determine the resource allocation indication based on real-time data transmission performance of the terminal and feedback information of the AP, so that the terminal device can better meet a requirement indicated by the resource allocation objective in a next scheduling period, thereby improving resource utilization.