Dynamic Radio Scheduler Metric Selection for 5G QoS Adaptation
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Solution Overview
Problem
Current radio communication networks, particularly 5G networks, lack flexibility and high performance in radio scheduling due to vendor-specific, homogeneous radio schedulers that can only react to dynamic situations based on distributed software schemes, limiting their ability to adapt to varying service level agreements (SLA), quality-of-service (QoS) requirements, and traffic demands.
Innovation Solution
Implementing a radio communication network with a database of diverse scheduling metrics that can be dynamically configured for each base station or cluster, allowing for flexible and temporary application of scheduling and inter-cell interference coordination (ICIC) schemes based on monitored performance information and service requirements, enabling geographical and temporal adaptability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a unique vendor-specific radio scheduler is implemented in base stations, then the scheduler can support multiple features such as frequency selective scheduling, inter-cell interference coordination, and quality-of-service awareness, but the scheduler lacks flexibility and cannot dynamically adapt to varying service level agreements, quality-of-service requirements, and traffic demands
Solution Approach 1:
The patent implements dynamic adaptability by enabling the radio scheduler to dynamically select and switch between different scheduling metrics based on current network conditions, traffic demands, and QoS requirements. The scheduler transitions from a static, vendor-specific implementation to a dynamic system that can adapt its behavior in real-time through metric selection from a database of available metrics
Solution Approach 2:
The patent creates a universal scheduling framework that can handle multiple different scheduling scenarios and requirements through a single scheduler implementation. By providing a database of diverse scheduling metrics and enabling selection based on service type and network conditions, the system achieves multi-functionality without requiring separate vendor-specific schedulers for different scenarios
2Productivity
If homogeneous scheduling software is used in base stations, then the scheduler can be updated with vendor software updates, but the scheduler can only react to dynamic situations based on distributed software schemes and cannot provide high-performance flexible scheduling
Solution Approach 1:
The patent segments the scheduling functionality by separating the scheduling metric selection from the base scheduler implementation. The scheduling metrics are stored in a database and can be independently selected and updated without modifying the core scheduler software, enabling flexible strategy changes while maintaining a stable scheduling framework
Solution Approach 2:
The patent enables flexible scheduling by allowing changes in scheduling parameters through metric selection rather than software updates. The system can switch between different scheduling metrics (e.g., proportional fair, maximum throughput, QoS-aware metrics) by changing the selected parameter set, providing high-performance flexible scheduling without requiring homogeneous software updates across all base stations
3Adaptability or versatility
If vendor-specific scheduling algorithms are deployed, then the scheduler can operate with distributed software schemes, but the system lacks the capability to dynamically configure different scheduling metrics based on monitored performance information
Solution Approach 1:
The patent implements feedback-driven dynamic configuration by continuously monitoring network performance information and using this feedback to select appropriate scheduling metrics. The system monitors QoS parameters, traffic patterns, and network conditions, then dynamically configures the scheduling metric to optimize performance based on the monitored feedback, closing the loop between performance monitoring and scheduling configuration
Data Source
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AI summary
The disclosure relates to a radio communication network (100), comprising: at least one base station (101) configured to transmit a data flow (102) to at least one user equipment (UE) (103) by using radio resources (104) scheduled to the at least one base station (101) for transmission of the data flow (102); a radio scheduler (105) configured to schedule the radio resources (104) to the at least one base station (101) according to a scheduling metric (107); a monitoring entity (109), configured to monitor performance information (106) from the at least one base station (101); and a controller (111), configured to adjust (108) the scheduling metric (107) of the radio scheduler (105) based on the monitored performance information (106) of the monitoring entity (109); and a data base (207) configured to store a plurality of scheduling metrics (208), wherein the controller (201) is configured to replace the scheduling metric (107) with one of the scheduling metrics (208) stored in the data base (207) or with a combination of scheduling metrics (208) stored in the data base (207).