Flow Control Entity Compensation Factor for Scheduler Buffer Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current communication network systems face performance degradation due to bottlenecks in the transport network and air interface, leading to inefficient use of scheduler buffers, especially during handovers and fluctuations in user equipment mobility, where existing flow control algorithms often overestimate or underestimate buffer requirements, resulting in empty or overloaded queues and reduced throughput.
Innovation Solution
A method and arrangement that compensates capability allocation messages with a first compensation factor based on scheduling policy, mobility, and radio channel type to optimize scheduler buffer usage, reducing the probability of buffer emptiness and improving flow control performance by adjusting capacity allocation and packet transmission timing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If flow control algorithm uses fixed capability allocation messages, then implementation is simple, but scheduler buffer utilization is suboptimal during mobility and handovers
Solution Approach 1:
The flow control algorithm dynamically adjusts the capability allocation message by applying a compensation factor that varies based on scheduling policy, mobility state, and radio channel type. This transforms the fixed allocation into a dynamic one that adapts to changing network conditions, resolving the contradiction between simple implementation and optimal buffer utilization.
Solution Approach 2:
The invention changes the parameter of capability allocation by introducing a compensation factor that modifies the base capability allocation message. This parameter adjustment allows the system to optimize scheduler buffer usage under different conditions (scheduling policies, mobility states, radio channel types) without fundamentally changing the flow control mechanism structure.
2Reliability
If capability allocation is increased to prevent buffer emptiness, then scheduler buffer utilization improves, but transport network congestion increases
Solution Approach 1:
The compensation factor is tailored to specific local conditions including scheduling policy type, mobility state, and radio channel type. This localized adjustment ensures that capability allocation is optimized for each specific scenario rather than applying a uniform increase, preventing unnecessary transport network congestion while maintaining buffer reliability.
Solution Approach 2:
The flow control mechanism uses feedback from the current network state (scheduling policy, mobility indicators, radio channel conditions) to adjust the capability allocation message. This feedback loop ensures that the allocation is increased only when and where necessary to prevent buffer emptiness, avoiding unnecessary increases that would cause transport network congestion.
3Productivity
If flow control adjusts capacity allocation dynamically, then buffer utilization optimizes, but message signaling overhead increases
Solution Approach 1:
The invention achieves dynamic buffer optimization by changing parameters within the existing capability allocation message framework rather than introducing entirely new signaling mechanisms. The compensation factor modifies the existing message structure, maintaining compatibility while enabling dynamic adjustment, thus minimizing additional signaling overhead.
4Measurement precision
If capability allocation message is compensated based on multiple factors, then flow control accuracy improves, but calculation complexity increases
Solution Approach 1:
The compensation factor calculation is segmented into distinct components based on scheduling policy, mobility state, and radio channel type. Each component can be calculated and adjusted independently, then combined to form the total compensation factor. This segmentation reduces calculation complexity compared to a monolithic approach while maintaining high accuracy.
Solution Approach 2:
The compensation mechanism applies different adjustment strategies tailored to specific local conditions (different scheduling policies, mobility states, radio channel types). This localized approach improves accuracy for each specific scenario while keeping the calculation complexity manageable by only considering relevant factors for each condition rather than all factors simultaneously.
Data Source
AI summary
The present invention relates to a method and an arrangement in a communication network node (15) of achieving an optimal use of a scheduler buffer for a given user equipment (18) communicating with said first communication network node (15). Said communication network node (15) comprising a flow control entity (83) adapted to control the flow of data in respect of said given mobile terminal (18) between a second communication network node (10) and said first communication network node (15) in a communication network system. The method comprises the step of providing, to a capability allocation message used for controlling the flow of data in respect of said given mobile terminal (18) between said second compensation network node (10) and said first communication network node (15) in said communication network system, a first compensation factor based on at least one of: scheduling policy, mobility, load and radio channel type.