RET Control via Spatial Beam Distribution Analysis
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Solution Overview
Problem
Current remote electrical tilt (RET) control methods in cellular networks lack efficiency in directing antenna tilt adjustments based on spatial distribution and channel conditions, leading to suboptimal cell coverage and interference management.
Innovation Solution
A method that involves obtaining beam reports from terminal devices, determining spatial distribution, and using machine learning processes to classify beam candidates and adjust antenna tilt angles, ensuring optimal coverage and minimizing interference by directing RET control based on the spatial distribution and channel conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional RET control methods are used, then the system is simple to operate, but the network efficiency and coverage optimization are insufficient
Solution Approach 1:
The system enables self-service by having terminal devices autonomously measure beam qualities and report spatial distribution information to the network entity. The network entity then automatically determines boundaries and generates RET control information without manual intervention, allowing the system to optimize itself based on real-time conditions while maintaining operational simplicity.
Solution Approach 2:
The patent implements feedback mechanisms where terminal devices continuously report beam quality measurements and spatial distribution data to the network entity. This feedback loop enables the network entity to dynamically adjust RET control information based on actual network conditions, improving network efficiency through data-driven optimization while keeping the control process automated and simple.
2Reliability
If beam reports and spatial distribution analysis are implemented, then cell coverage and interference management are improved, but the processing complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the serving area into multiple regions based on spatial distribution of beam candidates. The network entity determines boundaries that segment the area into zones with similar channel characteristics, allowing for region-specific RET optimization. This segmentation approach improves coverage and interference management by treating different areas differently, while the automated boundary determination keeps processing manageable.
Solution Approach 2:
The patent implements local quality by determining RET control information specific to each segmented region based on local spatial distribution characteristics. Different boundaries and control parameters are applied to different areas of the serving cell according to their specific channel conditions and beam candidate distributions, optimizing performance locally rather than using uniform control across the entire cell.
3Measurement precision
If machine learning processes are used to determine boundaries, then the precision of spatial distribution classification is improved, but the computational requirements and time increase
Solution Approach 1:
The patent applies partial action by implementing machine learning boundary determination selectively rather than continuously. The network entity uses ML processes to determine boundaries when needed for optimization, while relying on other control mechanisms during normal operation. This approach achieves high classification precision when required while minimizing the time loss associated with continuous ML processing.
4Object-generated harmful factors
If RET control is dynamically adjusted based on beam reports, then interference management is improved, but the system complexity and energy consumption increase
Solution Approach 1:
The patent implements periodic action by having terminal devices report beam quality measurements at specific intervals rather than continuously. The network entity uses these periodic reports to update spatial distribution information and adjust RET control accordingly. This periodic measurement and control approach effectively manages interference while significantly reducing energy consumption compared to continuous monitoring and adjustment.
Data Source
AI summary
Methods and apparatuses for remote electrical tilt (RET) control are disclosed. According to an embodiment, a network entity obtains beam reports indicating beam candidates suitable for serving terminal devices in a serving area of an access network node. The network entity determines a spatial distribution of the beam candidates based on the beam reports. The network entity determines one or more boundaries dividing the beam candidates into a plurality of groups, based on the spatial distribution. The network entity determines control information related to RET for an antenna array of the access network node, based on the one or more boundaries.