Network Node Small Cell Classification via Power Levels
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Solution Overview
Problem
Existing network technologies lack the ability to differentiate between macro cells and small cells, which hinders efficient inter-frequency load balancing and optimization of network performance.
Innovation Solution
A method in a network node that classifies neighbor cells by obtaining power level information from wireless devices and determining the relation between the source cell and neighbor cell power levels, using Reference Signal Received Power (RSRP) and power level distribution to identify small cells without requiring communication with other nodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the network node obtains power level information from wireless devices to classify neighbor cells, then the ability to identify small cells is improved, but the device complexity increases
Solution Approach 1:
The network node utilizes power level information that is already being measured and reported by wireless devices as part of their normal operation. The network node processes this existing data to classify neighbor cells, avoiding the need for additional measurements or complex interactions with other network nodes. This self-service approach enables small cell identification while minimizing added complexity.
2Productivity
If the network node classifies neighbor cells using power level distribution, then load balancing capability is improved, but the measurement precision requirements increase
Solution Approach 1:
The network node analyzes changes in power level parameters across different neighbor cells and uses these parameter variations to distinguish between macro cells and small cells. By examining how power levels distribute across multiple measurements and comparing them against threshold values, the network node achieves effective cell classification without requiring extremely precise measurements, thus enabling load balancing while maintaining reasonable measurement accuracy requirements.
3Device complexity
If the network node determines cell type based on power level relations, then the need for inter-node communication is reduced, but the reliability of classification may worsen
Solution Approach 1:
The network node continuously monitors power level information reported by wireless devices and uses this feedback to dynamically classify neighbor cells. By comparing current power level measurements against stored threshold values and historical data, the network node can adjust its classifications in real-time, improving reliability despite the reduced communication overhead. The feedback mechanism allows the system to adapt to changing network conditions without requiring extensive inter-node communication.
Data Source
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AI summary
The present disclosure relates to a method performed in a network node for classifying a neighbour cell. The method comprises the steps of obtaining (P1) from a plurality of wireless devices information related to a power level for a source cell and a power level for at least one neighbour cell, and determining (P5) whether the at least one neighbour cell is a small cell, based on the obtained information. The present disclosure further relates to such network node.