Multiple Threshold Scheduler for Wireless Fairness
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Solution Overview
Problem
Existing wireless communication schedulers fail to provide adaptive scheduling criteria that optimize throughput while ensuring fairness among users, particularly in multi-carrier systems, leading to inefficient resource allocation and poor Quality of Service (QoS) for users with poor channel conditions.
Innovation Solution
The proposed solution involves using standard deviation calculations to measure throughput spread among mobile terminals, adjusting scheduling criteria to prioritize lower throughput terminals during high spread conditions and maximizing overall throughput during low spread conditions, incorporating maximum carrier-to-interference ratio (CIR) and proportional fairness scheduling techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If scheduling prioritizes users with better channel conditions to maximize system throughput, then overall system throughput is improved, but fairness among users deteriorates
Solution Approach 1:
The scheduler dynamically adapts its behavior based on real-time channel conditions and queue states. When channel conditions are good, it prioritizes throughput maximization; when conditions deteriorate or fairness metrics indicate imbalance, it shifts to protecting users with poor channel conditions, creating a dynamic balance between throughput and fairness
Solution Approach 2:
The system changes scheduling parameters (prioritization weights, threshold values) based on current system state. By adjusting these parameters dynamically, the scheduler can shift between throughput-optimized mode and fairness-optimized mode, resolving the contradiction between maximizing throughput and ensuring fairness
2Reliability
If scheduling prioritizes users with worse channel conditions to ensure fairness, then fairness among users is improved, but system throughput deteriorates
Solution Approach 1:
The scheduler applies different scheduling strategies to different user groups based on their local conditions. Users with poor channel conditions receive protected treatment (higher priority) when needed, while users with good conditions are scheduled efficiently for throughput maximization, allowing fairness and throughput to coexist through localized quality adjustments
3Productivity
If a single scheduling criterion is used to maximize throughput, then system throughput is optimized, but adaptability to varying channel conditions deteriorates
Solution Approach 1:
The scheduler transitions from a static single-criterion approach to a dynamic multi-criterion system that adapts its behavior based on real-time channel conditions, user queue states, and fairness metrics, thereby achieving both throughput optimization and adaptability to varying conditions
4Reliability
If rudimentary scheduling criteria are used to provide fairness, then fairness among users is improved, but system throughput deteriorates
Solution Approach 1:
The system employs sophisticated parameter adjustment mechanisms that modify scheduling weights and priorities based on current system state. This allows the scheduler to achieve fairness through intelligent parameter tuning rather than crude equal-time-slot allocation, thereby maintaining both fairness and high throughput
Data Source
AI summary
The present invention provides different scheduling criteria depending on overall system performance in an effort to maintain fairness among mobile terminals and sustain a required QoS level. The invention is particularly effective for multi-carrier systems, wherein scheduling must also take into consideration the carrier used to transmit the scheduled data. In one embodiment, the present invention determines the spread of throughput rates for all mobile terminals being served by a given base station and bases the scheduling criteria thereon. Preferably, a standard deviation calculation is used to measure the throughput spread. The standard deviation of throughput associated with a collective group of mobile terminals is indicative of the differences between the lowest and highest throughputs with respect to the average throughput for the collective group of mobile terminals.