Terminal Reference Signal Configuration Control for Resource Efficiency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current radio communication technologies face challenges in efficiently utilizing reference signal (RS) resources, which is crucial for achieving high communication throughput and quality, especially with the integration of artificial intelligence (AI) and machine learning (ML) for network control and management.
Innovation Solution
A terminal and base station system that includes a receiving section for receiving reference signal configurations and a control section that dynamically controls the application of these configurations based on specific conditions and information related to the reference signal, optimizing RS resource allocation and use.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If reference signal resources are reduced to improve resource efficiency, then resource utilization improves, but communication throughput and quality may deteriorate
Solution Approach 1:
The patent applies dynamics by enabling the terminal to dynamically select between multiple reference signal configurations (first configuration with more resources, second configuration with fewer resources) based on real-time conditions such as AI/ML learning completion status and channel state. This dynamic adaptation allows the system to optimize resource efficiency while maintaining communication quality when needed.
Solution Approach 2:
The patent implements parameter changes by modifying reference signal resource allocation parameters based on different operating conditions. When AI/ML learning is completed or channel conditions are good, the system switches to a configuration with reduced reference signal resources. When learning is not completed or conditions deteriorate, the system switches to a configuration with more reference signal resources, thereby balancing resource efficiency and communication quality.
2Productivity
If reference signal resources are reduced using AI/ML, then resource efficiency improves, but implementation complexity increases due to undefined details
Solution Approach 1:
The patent applies segmentation by dividing the reference signal resource allocation into distinct configurations (first configuration and second configuration) with different resource levels. The terminal selects the appropriate configuration based on predefined conditions such as AI/ML learning status and channel state, thereby simplifying the implementation by avoiding the need for complex continuous optimization algorithms.
Solution Approach 2:
The patent implements self-service by enabling the terminal to autonomously select between reference signal configurations based on its own state (AI/ML learning completion status) and received channel state information, without requiring complex centralized control or detailed predefined algorithms for every scenario.
3Adaptability or versatility
If multiple reference signal configurations are maintained for different conditions, then adaptability improves, but device complexity increases
Solution Approach 1:
The patent applies segmentation by creating distinct reference signal configurations for different operating conditions (first configuration for when AI/ML learning is not completed or channel conditions are poor, second configuration for when learning is completed or conditions are good). This segmentation allows the system to maintain multiple configurations without requiring complex real-time optimization, as the terminal simply selects from predefined options based on simple condition checks.
Data Source
AI summary
A terminal according to one aspect of the present disclosure includes a receiving section that receives one or more reference signal configurations, and a control section that controls, based on at least one of information related to a reference signal and a specific condition, application of at least one reference signal configuration of the reference signal configurations. According to one aspect of the present disclosure, it is possible to implement suitable RS resource use.