Base Station Scheduling for SU-MIMO and MU-MIMO Fairness
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Solution Overview
Problem
Current communication systems face challenges in efficiently allocating resources to a diverse set of users with varying data requirements and priorities, particularly in handling both SU-MIMO and MU-MIMO users, which complicates scheduling and affects spectral efficiency and fairness among users.
Innovation Solution
A method for resource allocation by a base station that segregates users into SU-MIMO and MU-MIMO groups based on buffer occupancy and CSI feedback, using a proportional fair metric to prioritize and schedule users, allowing for efficient resource distribution across frequency and maintaining fairness among users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If users are treated uniformly in resource allocation, then scheduling is simple, but spectral efficiency and fairness deteriorate due to diverse user requirements
Solution Approach 1:
The patent segments users into different groups based on their data requirements and priorities. Specifically, it divides users into SU-MIMO (Single User Multiple Input Multiple Output) users and MU-MIMO (Multi User Multiple Input Multiple Output) users, and further segments them based on buffer occupancy levels. This segmentation allows the base station to apply different resource allocation strategies to different user groups, improving spectral efficiency while maintaining manageable scheduling complexity through structured classification.
2Productivity
If resource allocation considers diverse user parameters, then spectral efficiency improves, but scheduling complexity increases
Solution Approach 1:
The patent applies local quality by tailoring resource allocation parameters and strategies to specific user groups rather than applying a uniform approach. Different groups (SU-MIMO vs. MU-MIMO, high buffer vs. low buffer users) receive customized allocation schemes based on their local characteristics and requirements, optimizing spectral efficiency for each group while managing overall system complexity.
Solution Approach 2:
The patent utilizes parameter changes by dynamically adjusting resource allocation decisions based on user-specific parameters such as buffer occupancy, channel quality indicators (CQI), and priority levels. The base station modifies allocation parameters like resource block assignment, modulation and coding schemes, and transmission power according to the current state of each user group, thereby improving spectral efficiency through adaptive parameter optimization.
3Productivity
If users are segregated into groups, then resource allocation efficiency improves, but system complexity increases
Solution Approach 1:
The patent implements segmentation by dividing the user population into distinct groups based on their communication requirements, buffer occupancy, and MIMO capabilities. This structured segmentation enables the base station to apply specialized resource allocation algorithms to each group, improving overall allocation efficiency while containing system complexity through organized user classification and group-specific processing.
Data Source
AI summary
Embodiments of the present disclosure relates to a method for allocating resources to a plurality of users by a base station in a communication network. The method comprises obtaining a plurality of parameters associated with each of the plurality of users. The plurality of parameters is at least one of a buffer occupancy, a channel quality, and a channel state information acquisition capability. Also, the method comprises segregating the users into a plurality of groups using at least one of the plurality of parameters, wherein each group comprises one or more users. Further, the method comprises obtaining a group specific metric for each of the plurality of groups using at least one of the plurality of parameters, and allocating resources to the one or more users of the plurality of groups using the group specific metric.