Adaptive Cell Detection Counter for Radio Resource Optimization
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Solution Overview
Problem
User Equipment (UE) spends unnecessary radio time and resources on detecting cells with poor coverage, as existing methods require a fixed number of measurement attempts regardless of the cell's signal strength, leading to inefficient use of radio resources.
Innovation Solution
Adapting the maximum number of cell detection attempts based on network environment parameters, such as previous signal levels and locations, to quickly identify cells with stable service and reduce unnecessary attempts on weak cells.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fixed number of measurement attempts is used for cell detection, then the UE can ensure sufficient confidence in cell detection, but the UE spends unnecessary radio time and resources on detecting cells with poor coverage
Solution Approach 1:
The patent applies dynamics by making the maximum number of cell detection attempts adaptive rather than fixed. The counter maximum is dynamically adjusted based on the detected signal level (RSCP) of the neighboring cell, where stronger signals result in lower maximum attempt values. This dynamic adaptation allows the system to reduce measurement attempts for strong cells while maintaining sufficient attempts for weak cells, thereby resolving the contradiction between detection reliability and radio time consumption.
Solution Approach 2:
The patent changes the parameter of maximum detection attempts based on the signal level parameter. By establishing a relationship between RSCP values and maximum attempt counters (e.g., stronger signals → lower maximum attempts), the system optimizes measurement resources. This parameter change approach allows the UE to adapt its detection strategy to actual signal conditions, reducing unnecessary measurements on strong cells while ensuring adequate detection efforts on weak cells.
2Reliability
If a fixed number of measurement attempts is used for cell detection, then the UE can detect weak cells with sufficient confidence, but the UE consumes more power due to unnecessary measurement repetitions
Solution Approach 1:
The patent applies dynamics by making the maximum number of cell detection attempts adaptive rather than fixed. The counter maximum is dynamically adjusted based on the detected signal level (RSCP) of the neighboring cell, where stronger signals result in lower maximum attempt values. This dynamic adaptation allows the system to reduce measurement attempts for strong cells while maintaining sufficient attempts for weak cells, thereby resolving the contradiction between detection reliability and radio time consumption.
Solution Approach 2:
The patent changes the parameter of maximum detection attempts based on the signal level parameter. By establishing a relationship between RSCP values and maximum attempt counters (e.g., stronger signals → lower maximum attempts), the system optimizes measurement resources. This parameter change approach allows the UE to adapt its detection strategy to actual signal conditions, reducing unnecessary measurements on strong cells while ensuring adequate detection efforts on weak cells.
3Measurement precision
If the UE carries out multiple measurement occasions on each carrier, then the UE can find cells at minimum power level, but the strain on limited radio resources increases
Solution Approach 1:
The patent changes the parameter of maximum detection attempts based on the signal level parameter. By establishing a relationship between RSCP values and maximum attempt counters (e.g., stronger signals → lower maximum attempts), the system optimizes measurement resources. This parameter change approach allows the UE to adapt its detection strategy to actual signal conditions, reducing unnecessary measurements on strong cells while ensuring adequate detection efforts on weak cells.
Solution Approach 2:
The patent applies local quality by treating different neighboring cells differently based on their signal characteristics. Strong cells (high RSCP) receive fewer maximum measurement attempts, while weak cells (low RSCP) receive more attempts. This differentiated approach optimizes radio resource usage by allocating measurement efforts according to the specific needs of each cell, rather than applying a uniform measurement strategy to all cells.
Data Source
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AI summary
A user equipment (100) comprising a radio frequency communication interface (130), a memory (120) and a controller (110), said user equipment (100) being serviced by a servicing cell (210) and wherein said controller (110) is configured for detecting a neighbouring cell (220) by attempt to detect a signal over a radio frequency, determine if a signal is received over said radio frequency, and, if so, determine a detected cell based on said signal being received over said radio frequency and identify said detected cell as a neighbouring cell; and, if not, increase a attempt counter, said attempt counter indicating a number of attempts to detect a signal over said radio frequency. The UE is further configured to determine whether said attempt counter equals a maximum number of attempts and if so, determine that no cell is present on said radio frequency; and, if not attempt to detect a signal over a radio frequency again. The user equipment (100) is characterized in that said maximum number of attempts is associated with a network environment parameter.