Location-Aware UE Band Selection for Cellular Connection Reliability
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Solution Overview
Problem
Existing cellular networks face issues with non-optimal network planning and configuration, leading to localized performance problems such as call drops and connection failures, which are not effectively addressed by current technologies.
Innovation Solution
Implementing a UE-based smart band selection method that utilizes data collection and map exploitation to identify problematic locations and improve network performance by reducing connection failures, providing fast recovery from failures, and identifying coverage holes through learning-based approaches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional network planning and configuration methods are used, then network deployment is simpler, but localized performance problems such as call drops and connection failures occur
Solution Approach 1:
The UE autonomously detects performance degradation events, identifies problematic locations using its own measurement data and location information, and performs band selection without network intervention. This self-service mechanism resolves the contradiction by enabling the UE to independently improve connection reliability through event-driven band switching based on locally collected data, eliminating the need for complex network-side detection and configuration systems.
Solution Approach 2:
The system implements a feedback loop where the UE continuously monitors network performance metrics, compares them against thresholds, and triggers band selection changes when degradation is detected. The UE uses location information and measurement data to identify problematic areas and adjusts band selection accordingly, creating a closed-loop feedback system that improves connection reliability while keeping the overall system architecture relatively simple.
2Reliability
If UE autonomously performs band selection based on location and events, then connection failures are reduced, but processing complexity in UE increases
Solution Approach 1:
The UE pre-collects measurement data and location information during normal operation, building a database of network conditions at different locations before performance problems occur. When an event is detected, the UE can quickly reference this pre-collected data to identify the problematic location and select an appropriate band, rather than performing complex analysis in real-time. This preliminary data collection reduces the processing burden during critical events.
Solution Approach 2:
The autonomous band selection function is segmented into distinct modules: event detection module that monitors performance metrics, location identification module that determines problematic areas using collected data, and band selection module that chooses appropriate frequency bands. This segmentation allows each module to perform its specific function with optimized complexity, reducing the overall processing burden on the UE while maintaining reliable connection performance.
3Reliability
If more measurement data is collected for accurate band selection, then network performance improves, but energy consumption increases
Solution Approach 1:
The UE performs measurement data collection and event detection at periodic intervals rather than continuously, reducing energy consumption while maintaining accurate network performance monitoring. The system uses event-triggered measurements where additional data collection occurs only when performance degradation is detected, combining periodic sampling with event-driven supplementation to balance measurement accuracy and energy efficiency.
Solution Approach 2:
The UE dynamically adjusts measurement parameters such as sampling rate, measurement frequency, and data collection intensity based on current network conditions and battery status. When performance is stable and battery level is high, the UE collects more comprehensive data. When performance degrades or battery is low, the UE reduces measurement intensity while maintaining critical monitoring, optimizing the trade-off between network performance improvement and energy consumption.
Data Source
AI summary
A user equipment (UE) includes a transceiver, and a processor operatively coupled to the transceiver. The processor is configured to detect an occurrent of an event, and determine whether the event is a qualifying event. The processor is also configured to, in response to a determination that the event is a qualifying event, identify, based on a band map and a present location of the UE, an event improvement procedure, and perform the event improvement procedure.