Co-scheduling Wireless Devices Using Angular Spread
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Solution Overview
Problem
Current communications networks face challenges in efficiently co-scheduling wireless devices in multi-user MIMO scenarios due to unreliable PMI reports and lack of specialized CSI feedback modes, leading to interference and suboptimal performance.
Innovation Solution
The method involves obtaining directional information and angular spread data for wireless devices to reject co-scheduling hypotheses when the angular spread conditions are met, thereby improving co-scheduling decisions and reducing interference by considering the propagation channel's angular characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If co-scheduling is performed without considering angular spread, then resource utilization increases, but interference between users increases and performance deteriorates
Solution Approach 1:
The system performs preliminary estimation of angular spread for each user before final scheduling decisions. This advance assessment allows the scheduler to identify users with compatible angular spreads beforehand, enabling better co-scheduling decisions that reduce interference while maintaining high resource utilization.
Solution Approach 2:
The system uses feedback from angular spread measurements to dynamically adjust scheduling decisions. By continuously monitoring angular spread characteristics and using this information to refine co-scheduling choices, the system optimizes the balance between resource utilization and interference management.
2Measurement precision
If angular spread estimation is performed for all users, then co-scheduling accuracy improves, but computational complexity increases
Solution Approach 1:
Instead of uniformly processing all users with the same level of detail, the system applies angular spread estimation selectively. Users are categorized based on their potential for co-scheduling, and angular spread analysis is performed with appropriate depth for each category, reducing overall computational complexity while maintaining accuracy where it matters most.
Solution Approach 2:
The system dynamically adjusts the precision of angular spread estimation based on scheduling context. When multiple co-scheduling candidates are available, more precise estimation is applied. When few candidates exist, simpler methods suffice, thereby adapting computational effort to actual needs and reducing unnecessary complexity.
Data Source
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AI summary
There is provided mechanisms for co-scheduling wireless devices in a communications network. A method is performed by a network node. The method comprises obtaining first directional information indicating direction of transmission to a first wireless device. The method comprises obtaining second directional information indicating direction of transmission to a second wireless device. The method comprises rejecting a hypothesis of co- scheduling the first wireless device and the second wireless device when at least one of the direction of the second wireless device and angular spread of the direction to the second wireless device is within angular spread of the direction to the first wireless device.