MU-MIMO Scheduling via Inverted Quality Selection
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Solution Overview
Problem
Conventional MU-MIMO grouping approaches fail to provide desirable performance in scenarios where each user requires sufficient throughput and robustness, particularly in industrial environments with many users and tight latency requirements, leading to unreliable communication.
Innovation Solution
A method for MU-MIMO scheduling that forms groups of receivers based on communication quality metrics, selecting members with lower quality metrics than the highest, ensuring sufficient communication quality and minimizing cross-talk, and scheduling transmissions to each group from corresponding transmission instances, while allowing for pre-operational semi-static grouping and periodic updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional MU-MIMO grouping approaches are used to group users for simultaneous transmission, then system throughput is improved, but communication reliability and robustness deteriorate in scenarios with many users and tight latency requirements
Solution Approach 1:
The patent changes the grouping parameter from maximizing throughput to ensuring robustness by selecting users with lower communication quality metrics. This parameter change resolves the contradiction by prioritizing reliability over throughput, achieving stable communication for all users including those with poorer channel conditions.
Solution Approach 2:
Instead of selecting users with highest communication quality for grouping (conventional approach), the patent inverts the selection criterion to choose users with lower quality metrics. This inversion ensures that users who would otherwise be excluded from MU-MIMO groups are included, improving overall communication reliability and robustness.
2Productivity
If user grouping is performed to enable simultaneous MU-MIMO transmission, then spectral efficiency is improved, but computational complexity increases
Solution Approach 1:
The patent segments the user selection process into two stages: first identifying users who satisfy a minimum quality criterion, then selecting from those users based on lower quality metrics. This segmentation simplifies the overall computational complexity by breaking down the complex optimization problem into more manageable steps.
Solution Approach 2:
The patent changes the selection parameter from optimizing group performance to selecting individual users with lower quality metrics. This parameter change simplifies the computational approach while maintaining spectral efficiency, as the selection process becomes more straightforward and less computationally intensive.
3Reliability
If strict quality criteria are applied for user selection in MU-MIMO groups, then communication quality is improved, but the number of users that can be accommodated decreases
Solution Approach 1:
The patent inverts the traditional user selection approach by not excluding users with lower quality metrics, but rather actively selecting them for grouping. This inversion allows a larger number of users to be accommodated in MU-MIMO groups while maintaining sufficient communication quality through the robust grouping mechanism.
Solution Approach 2:
The patent creates a universal grouping mechanism that can accommodate users with diverse communication quality levels. By selecting users with lower quality metrics and providing them with robust grouping, the system achieves multi-functionality in serving both high-quality and low-quality users simultaneously, increasing the total number of accommodated users.
Data Source
AI summary
A multi-user multiple-input multiple-output (MU-MIMO) scheduling method is disclosed for scheduling transmission from a plurality of transmission instances to a plurality of receivers. The method comprises acquiring, for each pair of a transmission instance and a receiver, a communication quality metric and forming a first group of receivers from the plurality of receivers. The first group of receivers is formed by selecting a first receiver as a first group member and associating a first transmission instance to the first receiver and—when a plurality of communication quality metrics of the first transmission instance and not yet selected receivers fulfill a first criterion for sufficient communication quality—selecting a second receiver from the not yet selected receivers as a second group member and associating a second transmission instance to the second receiver. The communication quality metric of the first transmission instance and the second receiver fulfills the first criterion for sufficient communication quality and indicates a lower communication quality than the highest communication quality among the plurality of communication quality metrics that fulfill the first criterion for sufficient communication quality. The method also comprises forming at least a second group of receivers from the plurality of receivers by repeating the selection steps for receivers not included in the first group of receivers, and scheduling MU-MIMO transmission to the receivers of each group from the corresponding associated transmission instances. Corresponding apparatus, deployment server, and computer program product are also disclosed.