Antenna Configuration Adjustment via Cell State Analysis
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Solution Overview
Problem
Current self-organizing network (SON) solutions for coverage capacity optimization require accurate user equipment (UE) location and antenna configuration parameters, which are costly and not scalable to small cells and heterogeneous networks, due to the need for manual effort and drive testing.
Innovation Solution
A method and apparatus that determine cell states based on measurement reports from UE devices, performing analyses for coverage, interference, and quality to adjust antenna configuration parameters without requiring UE location or accurate antenna configuration information, using a closed-loop process with incremental and biased random adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If Automatic Cell Planner (ACP) is used for coverage capacity optimization, then accurate propagation modeling and user quality of experience can be achieved, but costly drive testing and manual verification are required
Solution Approach 1:
The system enables self-organizing networks where base stations automatically perform coverage capacity optimization using measurement reports from user equipment. The network self-adjusts antenna configuration parameters without requiring external drive testing or manual verification, making the system self-sufficient and eliminating the need for costly external optimization services.
Solution Approach 2:
The system implements a closed-loop feedback mechanism where measurement reports from user equipment are continuously collected and used to automatically adjust antenna configuration parameters. This feedback-driven approach replaces open-loop modeling methods with data-driven optimization, eliminating the need for separate verification steps while maintaining accuracy.
2Measurement precision
If ACP with UE geo-location data is used, then accurate cell state determination is possible, but the complexity of obtaining and processing location data increases
Solution Approach 1:
The invention extracts only the necessary measurement data (RSRP, RSRQ, interference metrics) from user equipment measurement reports, eliminating the need to collect and process unnecessary location data. By taking out only the essential parameters needed for cell state determination, the system reduces data collection and processing complexity while maintaining accuracy.
Solution Approach 2:
Instead of relying on actual UE location data which requires complex collection and processing infrastructure, the system uses measurement report data that inherently contains the necessary spatial information. This copying approach using proxy measurements simplifies the data infrastructure while preserving the ability to determine cell states accurately.
3Manufacturing precision
If manual configuration and verification is performed, then accurate antenna parameters can be set, but the process is not scalable to small cells and heterogeneous networks
Solution Approach 1:
The system enables each base station to automatically configure and optimize its own antenna parameters based on local measurement reports. This self-service capability eliminates the need for manual configuration and verification, making the process scalable to large numbers of small cells and heterogeneous networks without proportionally increasing manual effort.
Solution Approach 2:
The system implements dynamic, automated adjustment of antenna configuration parameters based on real-time measurement reports from user equipment. This dynamic approach replaces static manual configuration with adaptive automated optimization, enabling scalability to heterogeneous networks where conditions change frequently and manual reconfiguration would be impractical.
4Measurement precision
If drive testing is conducted for network optimization, then accurate coverage and quality measurements are obtained, but time and resource consumption increase significantly
Solution Approach 1:
The system implements continuous feedback loops using measurement reports from user equipment to automatically adjust antenna parameters. This real-time feedback mechanism eliminates the need for separate drive testing phases, as the optimization process continuously uses actual network operation data, significantly reducing the time required while maintaining measurement accuracy.
Solution Approach 2:
The system performs coverage and quality measurements continuously using ongoing user equipment measurement reports rather than conducting discrete drive testing campaigns. This continuous measurement approach provides up-to-date accuracy while eliminating the significant time loss associated with periodic manual testing and re-optimization.
Data Source
AI summary
A method for determining cell states to adjust antenna configuration parameters includes receiving, at a radio access nodes in a network, measurement reports from a plurality of user equipment devices. The radio access node performs a weak coverage analysis in response to the measurement reports to determine whether a cell provided by the radio access node is assigned a good coverage state or a weak coverage state. The radio access node performs an overshooting analysis in response to the measurement reports to determine whether the cell provided by the radio access node is assigned an overshooter state or a non-overshooter state. The radio access node performs an interference analysis in response to the measurement reports to determine whether the cell provided by the radio access node is assigned an interferer state or a non-interferer state. The radio access node performs a quality analysis in response to the measurement reports to determine whether the cell provided by the radio access node is assigned a good quality state or a bad quality state. Adjustments are made to antenna configuration parameters of the cell provided by the radio access node in response to the various states assigned to the cell.