RAN Scheduling Service Optimizing Resource Allocation via Priority Values
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Solution Overview
Problem
Current radio access network (RAN) slicing approaches do not account for differences among end devices and their radio conditions, leading to unfair scheduling and inefficient resource utilization, resulting in service degradation for end devices with less favorable radio conditions.
Innovation Solution
A scheduling service that calculates a priority value for each end device based on instantaneous and average throughput values, and a RAN slice weight, to optimize resource allocation and scheduling in RAN slice environments, improving network resource utilization and quality of service.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If current RAN slicing approaches are used for scheduling, then network resource allocation is simplified, but fairness among end devices with different radio conditions deteriorates
Solution Approach 1:
The patent applies local quality by differentiating scheduling treatment based on individual end device radio conditions. Each end device receives customized scheduling parameters (priority values, RAN slice weights) tailored to its specific radio condition, rather than uniform treatment. This resolves the contradiction by maintaining simplified overall scheduling architecture while achieving fair local treatment for each device.
Solution Approach 2:
The patent changes scheduling parameters dynamically based on radio conditions. Priority values and RAN slice weights are adjusted according to measured radio condition metrics, allowing the system to adapt scheduling behavior without changing the fundamental scheduling mechanism. This enables fair resource allocation across devices with different radio conditions while maintaining scheduling simplicity.
2Ease of operation
If uniform scheduling is applied to all end devices in a RAN slice, then scheduling implementation is simplified, but resource utilization efficiency deteriorates
Solution Approach 1:
The patent introduces dynamics by making scheduling parameters adaptive rather than static. Priority values and RAN slice weights are updated based on current radio conditions and throughput measurements, allowing the system to respond to changing network states. This maintains ease of implementation through automated parameter adjustment while improving resource utilization efficiency.
3Reliability
If RAN slice weight is incorporated into priority calculation, then resource allocation fairness is improved, but calculation complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing RAN slice weights for different slices before scheduling decisions are made. These pre-computed weights are then readily available for incorporation into priority calculations, reducing the computational burden during real-time scheduling. This resolves the contradiction by preparing fairness parameters in advance, making the actual scheduling calculation more efficient.
Data Source
AI summary
A method, a device, and a non-transitory storage medium are described in which an scheduling service is provided. The scheduling service includes calculation of a priority value, on a per end device basis, based on throughput information and tuning parameter values. The priority value may also be calculated based on a radio access network slice weight. The scheduling service may calculate a schedule for transmission of data to an end device based on the priority value, available network resources, and a quality of service profile associated with a quality of service flow of the end device.