Neighbor List Optimization via Subcell Handover Frequency Analysis
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Solution Overview
Problem
The existing methods for creating and updating neighbor lists in mobile communication systems are inefficient and prone to errors due to manual data analysis and reliance on base station-specific statistics, leading to unreliable handover processes and call faults.
Innovation Solution
A method and apparatus that collect and analyze wireless quality measurement data and call fault data to generate source-target subcell combinations, count frequencies of successful and failed handovers, and prioritize target subcells for optimized neighbor list generation, enhancing handover reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If manual data analysis is used to create and update neighbor lists, then the process is simple to implement, but the reliability and accuracy of handover management deteriorates due to errors and time consumption
Solution Approach 1:
The system automatically collects wireless quality measurement data and call fault data, analyzes it to generate source-target subcell combinations, and updates the neighbor list without manual intervention. The network self-optimizes handover parameters by utilizing its own operational data, eliminating human error while maintaining simplicity through automated processes.
Solution Approach 2:
The system continuously collects call fault data and wireless quality measurements, analyzes this feedback information to identify handover failures, and automatically updates the neighbor list to prevent recurring failures. This closed-loop feedback mechanism improves handover reliability by learning from past failures and adapting the neighbor list accordingly.
2Device complexity
If neighbor list is updated in units of base station using PN statistics, then the update process is simplified, but the accuracy deteriorates because statistics information of PN not related to the base station cannot be provided
Solution Approach 1:
The system segments the neighbor list update process by subcell rather than base station, creating source-target subcell combinations that provide granular, accurate handover information. This segmentation allows each subcell to have its own optimized neighbor list based on specific wireless quality measurements and call fault data, improving precision without excessive complexity.
Solution Approach 2:
The system applies local quality optimization by generating customized neighbor lists for each source subcell based on local wireless quality measurement data and call fault statistics. Each subcell receives tailored handover parameters specific to its local conditions rather than generic base station-level parameters, enhancing accuracy for local handover scenarios.
3Ease of operation
If handover statistics information in units of base station is used to determine priority, then the process is straightforward, but the reliability of the neighbor list deteriorates due to restricted analysis scope
Solution Approach 1:
The system segments handover statistics from base station level to subcell level, enabling more granular analysis of handover patterns. By counting frequencies at the subcell level and generating source-target subcell combinations, the system achieves more reliable neighbor lists while maintaining operational simplicity through automated frequency counting and priority assignment.
Solution Approach 2:
The system adds a new dimension of analysis by considering subcell-level handover statistics rather than only base station-level data. This dimensional change from base station to subcell granularity enables more precise identification of handover patterns and improves neighbor list reliability while keeping the process straightforward through systematic data collection and analysis.
4Measurement precision
If accurate location information of base stations is required for verification, then the accuracy of neighbor list improves, but the complexity and difficulty of verification increases significantly
Solution Approach 1:
The system automatically collects and verifies location information through wireless quality measurement data without requiring manual verification. The automated data collection and analysis process handles location verification as part of the normal operation, reducing complexity while maintaining accuracy through systematic processing of measurement data.
Data Source
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AI summary
A method and an apparatus for optimizing a neighbor list in a mobile communication system. The apparatus in accordance with an embodiment of the present invention can include: a data collecting unit, collecting wireless quality measurement data and call fault data of a mobile communication terminal, wherein the call fault data is information on a call fault event generated because no subcell information is present in the neighbor list when the mobile communication terminal carries out a handover; a data analyzing unit, analyzing the wireless quality measurement data and the call fault data and calculating a frequency of a subcell being included in an active set for each handover-possible target subcell and a frequency of call fault event occurrence, wherein the frequency of being included in the active set is a frequency of the subcell and target subcell being included simultaneously in the active set for handover; and a neighbor list optimizing unit, using the frequency of being included in the active set and the frequency of call fault event occurrence to set an order of priority of handover-possible target subcells for the subcell and generating a neighbor list.