Gaussian Weighted Scheduling for MIMO Fairness
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing scheduling methods in downlink wireless communication systems with MIMO antennas fail to ensure fairness between terminals and control transmission rates effectively, particularly for terminals with low average Signal to Interference and Noise Ratio (SINR), leading to inadequate minimum required transmission rates.
Innovation Solution
A generalized Proportional Fair (PF) scheduling algorithm that approximates instantaneous transmission rate distribution to a Gaussian distribution, determines weights for each terminal to satisfy target transmission rates, and selects terminal sets based on these weights to regulate fairness and transmission rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If Proportional Fair scheduling algorithm is used to maximize system capacity and ensure proportional fairness, then transmission opportunity is distributed fairly among terminals, but terminals with low average SINR cannot ensure minimum required transmission rate
Solution Approach 1:
The patent modifies the scheduling algorithm by introducing a new parameter 'target transmission rate' that can be adjusted based on terminal conditions. The scheduler calculates a modified weight for each terminal by comparing its average transmission rate to the target rate, thereby changing the selection criteria to ensure minimum rate guarantees while maintaining system capacity efficiency
2Reliability
If Proportional Fair scheduling algorithm is used to distribute transmission opportunity equally, then all terminals get fair access, but terminals with very good channel state receive excessive transmission opportunity
Solution Approach 1:
The patent applies different weighting strategies to different terminals based on their individual characteristics. Terminals with better channel conditions receive adjusted weights that prevent excessive allocation, while terminals with poorer conditions receive boosted weights to ensure minimum rates. This localized differentiation maintains overall fairness while optimizing transmission rate distribution
Data Source
AI summary
A scheduling method in a wireless communication includes receiving a Channel Quality Indicator (CQI) from a plurality of terminals. The method also includes determining an average transmission rate of each terminal based on the CQI by approximating an instantaneous transmission rate distribution to a Gaussian distribution. The method further includes determining a weight of each terminal such that the average transmission rate of each terminal satisfies a target transmission rate. The method also includes selecting a terminal set by applying the determined weight. Thus, it is possible to control the fairness between the terminals and to efficiently control the transmission rate of the terminals according to the required transmission rate and the channel environment of the terminals.