Partially Network-Controlled Repeater Beam Management
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current wireless communications systems face challenges such as signal attenuation and blockage in complex environments, leading to inefficiencies in data transmission, power consumption, and network control overhead.
Innovation Solution
A partially network-controlled repeater that autonomously performs beam management decisions, including beamsweeping, beam selection, switching, refinement, and failure recovery without direct base station control, using machine learning models and reference signals for optimal communication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fully network-controlled repeater is used, then network control and coordination is improved, but device complexity and control overhead increase
Solution Approach 1:
The repeater autonomously performs beam management procedures including beamsweeping, beam selection, switching, refinement, and failure recovery without requiring direct base station control. The repeater uses machine learning models to make intelligent decisions about beam configuration and optimization, thereby reducing control overhead while maintaining reliable operation.
Solution Approach 2:
The control function is segmented between the network entity and the repeater. The network entity provides high-level configuration and resources, while the repeater handles autonomous beam management operations. This segmentation reduces the control burden on the network while maintaining overall system coordination.
2Productivity
If beam management is performed autonomously by the repeater, then communication efficiency and power consumption are improved, but measurement and detection difficulty increase
Solution Approach 1:
The repeater uses feedback from reference signals and beam failure detection to continuously optimize its beam management. When beam failure is detected, the repeater automatically initiates recovery procedures by selecting alternative beams based on feedback information from the user equipment and network entity.
Solution Approach 2:
The patent replaces complex mechanical beam switching mechanisms with machine learning-based autonomous decision-making. The repeater uses AI models to predict optimal beam configurations and automatically adjusts beams without requiring complex manual control mechanisms.
3Device complexity
If the repeater operates independently without base station control, then device complexity is reduced, but adaptability to network conditions deteriorates
Solution Approach 1:
The repeater dynamically adjusts its operation mode between autonomous beam management and network-controlled modes. It can switch between these modes based on network conditions, allowing it to maintain simplicity when operating independently while adapting to network requirements when coordination is needed.
Solution Approach 2:
The repeater is designed with multi-functionality, capable of performing both autonomous beam management and network-coordinated operations. This universal design allows the repeater to adapt to different operational contexts while maintaining relatively simple device architecture.
Data Source
AI summary
Certain aspects of the present disclosure provide techniques for a partially network-controlled repeater. A method for wireless communications by a repeater includes receiving downlink control information (DCI) from a network entity via a backhaul link, the DCI indicating a time period for beam management. The method includes performing a beam management procedure with a user equipment (UE) during the time period. The method includes determining a beam for communicating with the UE based on the beam management procedure. The method includes communicating with the UE using the beam.