UE Location Optimization for Adaptive Base Station Testing
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Solution Overview
Problem
Creating optimal propagation channels for base station testing is time-consuming and resource-intensive, and conditions can change over time, making it difficult to meet testing requirements.
Innovation Solution
A base station testing system that includes a plurality of UEs, a UE adjustment component, and processors to determine and adjust UE locations automatically, optimizing them to achieve optimal performance metrics through closed-loop techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual methods are used to create propagation channels for base station testing, then testing requirements can be met, but the process is time-consuming and resource-intensive
Solution Approach 1:
The system enables self-service by allowing the base station testing system to automatically determine and adjust UE locations without manual intervention. The processor autonomously calculates optimal locations based on initial locations and performance metrics, then controls the UE adjustment component to reposition UEs, eliminating the need for operator involvement while maintaining testing requirement fulfillment.
Solution Approach 2:
The system implements feedback by continuously measuring performance metrics at different UE locations and using this information to determine optimal locations. The processor evaluates performance data from initial locations, adjusts UE positions based on metric improvements, and iteratively refines locations until optimal testing conditions are achieved, creating a closed-loop control system that reduces time while ensuring requirements are met.
2Reliability
If manual adjustment of UE locations is performed, then propagation channels can be created, but the process requires extensive operator involvement and is difficult to adapt when conditions change
Solution Approach 1:
The system eliminates operator involvement by implementing self-service functionality where the processor automatically determines initial UE locations, calculates optimal locations based on performance metrics, and controls the UE adjustment component to reposition UEs. The entire propagation channel creation process occurs autonomously without requiring operator knowledge or manual adjustment, significantly improving ease of operation while maintaining reliable channel creation.
Solution Approach 2:
The system achieves adaptability through dynamic adjustment capabilities. When testing conditions change, the processor can重新 determine optimal UE locations by evaluating new performance metrics and controlling the UE adjustment component to reposition UEs accordingly. This dynamic response allows the system to adapt to changing conditions automatically without requiring operator intervention, making the process both easier to operate and more flexible.
3Productivity
If automated UE location optimization is implemented, then time and resource requirements are reduced, but system complexity increases
Solution Approach 1:
The system achieves high productivity through a multi-functional processor that combines initial location determination, performance metric evaluation, optimal location calculation, and UE adjustment control within a single device. This universal component performs multiple functions that would otherwise require separate systems, reducing overall system complexity while enabling automated location optimization and improving testing efficiency.
Data Source
AI summary
A base station testing system includes a plurality of user equipments (UEs), a UE adjustment component, and one or more processors. The one or more processors determine respective initial locations of the plurality of UEs with respect to a base station and cause the UE adjustment component to move the plurality of UEs to the respective initial locations. The one or more processors determine one or more candidate locations of each UE with respect to the base station and cause the UE adjustment component to move each UE to the one or more candidate locations of the UE. The one or more processors then determine respective optimal locations of the plurality of UEs with respect to the base station and cause the UE adjustment component to move the plurality of UEs to the respective optimal locations.