Predictive Score Scheduler for Wireless Resource Allocation
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Solution Overview
Problem
Current scheduling techniques for wireless communications face challenges in achieving a balance between sum-rate maximization and fairness, particularly when predicting future channel conditions and handling heterogeneous fading statistics, leading to suboptimal performance and unfairness in resource allocation.
Innovation Solution
The Predictive Score Based Scheduler (P-SBS) allocates channel resources by combining causal past measurements with anti-causal predicted future values, using a non-iterative approach that accounts for prediction uncertainty, thereby optimizing the trade-off between sum-rate and fairness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If predictive scheduling is used to maximize sum-rate, then throughput performance is improved, but fairness among users deteriorates
Solution Approach 1:
The patent transforms the scheduling decision from a direct channel-quality-based selection to a score-based selection where the score is derived from the cumulative distribution function (CDF) of channel quality. This parameter transformation ensures that users are selected based on their relative channel quality position rather than absolute values, maintaining fairness while enabling predictive sum-rate optimization. The CDF parameterization allows the system to account for heterogeneous fading statistics across users.
Solution Approach 2:
The patent performs preliminary computation of the CDF based on historical channel quality measurements before making scheduling decisions. By pre-computing the CDF from past observations, the system prepares a reference distribution that captures each user's channel characteristics, enabling fair and efficient real-time scheduling without exhaustive optimization during the scheduling instant.
2Productivity
If exhaustive numerical optimization is used for predictive scheduling, then sum-rate performance is improved, but computational complexity increases
Solution Approach 1:
The patent extracts the computationally intensive exhaustive optimization step from the real-time scheduling process and replaces it with a simpler score-based selection. The CDF-based scoring mechanism extracts only the essential information needed for fair scheduling without requiring complex numerical optimization, significantly reducing computational complexity while maintaining predictive performance benefits.
Solution Approach 2:
The patent uses a simple scoring function based on CDF values that can be computed efficiently and discarded each scheduling interval, replacing the need for expensive, complex optimization algorithms. This disposable scoring approach provides sufficient performance without the burden of maintaining complex optimization structures.
Data Source
AI summary
A scheduler (P-SBS) for scheduling the allocation of channel resources to users of a wireless communication system (BS; MS1, MS 2, ..., MS k) is configured for: - allotting to the users respective allocation scores as a function of at least one parameter of the channel resources, and - scheduling allocation of the channel resources to the users as a function of the allocation scores allotted thereto. The respective allocation scores are allotted as the sum of: - i) a causal function of past measurements of the parameter(s) of the channel resources, and - ii) an anti-causal function of future values of the parameter(s) of the channel resources.