Predictive Signal Quality in Base Station Handover
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Solution Overview
Problem
Current wireless communication systems face challenges in efficiently managing handovers between base stations, particularly due to uncertainties in signal quality predictions, which can lead to connection failures and re-establishment issues.
Innovation Solution
The implementation of predictive signal quality assessments to determine the likelihood of successful handovers, where predictions are included in handover request and response messages to decide whether to proceed with the handover, thereby reducing connection failures and re-establishment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If handover is performed based on current signal quality measurements, then handover can be executed quickly, but connection failures occur due to uncertain signal quality predictions
Solution Approach 1:
The system performs preliminary signal quality predictions and generates handover recommendations before the actual handover decision is made. The source base station receives prediction information from the target base station in advance, allowing it to evaluate multiple potential handover targets and prepare decision data before execution is required.
Solution Approach 2:
The system cushions against potential handover failures by incorporating predicted signal quality information and success probability assessments into the handover decision process. This allows the source base station to avoid handovers to targets with low predicted success rates, thereby preventing connection failures before they occur.
2Reliability
If predictive signal quality assessments are performed for all potential target base stations, then handover success rate improves, but signaling overhead and processing complexity increase
Solution Approach 1:
The system applies different levels of prediction detail to different target base stations based on local conditions. The source base station evaluates prediction information selectively for potential targets, focusing detailed analysis on those most likely to be chosen, rather than uniformly complex analysis for all possible targets.
Solution Approach 2:
The system changes the parameter of prediction information granularity, providing different levels of detail in prediction messages based on the specific scenario. Prediction information can include various parameters such as signal quality metrics, success probabilities, and timing information, allowing the system to adjust the complexity of information exchanged based on what is needed for the decision.
3Reliability
If handover is avoided when prediction indicates likely failure, then connection failures are reduced, but service continuity may be impacted due to delayed handover
Solution Approach 1:
The system dynamically adjusts handover timing and target selection based on real-time prediction information. When predictions indicate successful handover, the system executes quickly; when predictions indicate potential failure, the system delays or modifies the handover decision, allowing flexible adaptation to changing conditions.
Solution Approach 2:
The system uses feedback from prediction results to adjust handover decisions. The source base station receives prediction information from target base stations, evaluates this feedback against current conditions, and makes informed decisions about whether to proceed with handover, thereby avoiding failures while maintaining appropriate speed.
Data Source
AI summary
A base station may communicate with at least one other base station to perform a handover of a wireless device. Predictions of a signal quality may be used for the handover of the wireless device. Predictions of signal quality may be included in a handover request message and/or in a handover response message. A determination of whether to proceed with a handover of the wireless device to a target base station may be based on the predictions of signal quality.