UE Configuration via Context-Aware Beam Search Optimization
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Solution Overview
Problem
Current methods for configuring wireless communication links between User Equipment (UE) and base stations are inefficient, as they perform exhaustive beam searches regardless of the UE's specific use case, leading to increased battery consumption, latency, and reduced resource utilization.
Innovation Solution
The method involves detecting UE movement and context to predict and configure optimal communication parameters, such as beam selection and antenna usage, by distinguishing between purposed and non-purposed movements, thereby reducing unnecessary searches and optimizing resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional beam training algorithms such as exhaustive and repeated search are used to find the best transmit and receive beams, then communication reliability is improved, but battery consumption increases and latency increases
Solution Approach 1:
The system changes the parameter of beam search completeness by introducing context-based filtering. Instead of always performing exhaustive searches, the system adapts the search parameters based on UE context (movement state, service type, channel conditions), performing limited searches when context indicates stability and exhaustive searches only when necessary, thus reducing energy consumption while maintaining reliability when needed
Solution Approach 2:
The system performs preliminary context assessment before initiating beam training. By evaluating UE movement state, service requirements, and channel conditions in advance, the system pre-determines the appropriate search strategy, avoiding unnecessary exhaustive searches and reducing both energy consumption and latency
2Reliability
If traditional beam training algorithms such as exhaustive and repeated search are used to find the best transmit and receive beams, then communication reliability is improved, but latency increases
Solution Approach 1:
The system dynamically adjusts the beam search parameter (search depth and scope) based on context. When UE is stationary and channel conditions are stable, the system reduces search parameters to minimal necessary levels, significantly reducing latency. When movement or service requirements demand higher reliability, the system increases search parameters accordingly
Solution Approach 2:
The system performs preliminary context evaluation to predict the optimal beam configuration before actual data transmission begins. By assessing UE state and service requirements in advance, the system prepares appropriate beam configurations, reducing the time needed for beam training during active communication
3Use of energy by moving object
If context-based beam selection is used to reduce battery consumption and latency, then energy efficiency is improved, but device complexity increases
Solution Approach 1:
The system uses a universal context assessment mechanism that serves multiple functions: evaluating UE movement state, determining service requirements, assessing channel conditions, and predicting optimal beam configurations. This multi-functional approach consolidates what could be separate complex modules into a single integrated system, reducing overall device complexity while maintaining energy efficiency benefits
Data Source
AI summary
Methods and apparatus are provided. In an example aspect, method of configuring a User Equipment (UE) is provided. The method includes detecting a movement of the UE, determining a context of the UE in response to the detected movement, and configuring at least one parameter of wireless communication between the UE and a base station based on the context of the UE and the detected movement.