Communication Method for Environment-Adaptive Machine Learning
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Solution Overview
Problem
The integration of machine learning technology into mobile communication systems is hindered by the lack of established methods for effectively leveraging this technology, particularly in terms of using suitable learning data for each user equipment environment.
Innovation Solution
A communication method where environment data indicating the environmental state of a user equipment is associated with learning data, allowing the user equipment or base station to determine whether to perform machine learning using the learning data based on the environment, thereby ensuring the suitability of the learning data for the specific environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If machine learning technology is integrated into mobile communication systems, then the accuracy and effectiveness of machine learning operations is improved, but the suitability of learning data for specific user environments cannot be ensured
Solution Approach 1:
The patent applies local quality by associating environment data with learning data to ensure that each user equipment receives learning data suitable for its specific environment. The system determines suitability based on environmental characteristics such as location, movement speed, and communication conditions, thereby improving measurement precision while maintaining environmental adaptability.
2Productivity
If learning data is used without considering environmental factors, then the processing speed is maintained, but the accuracy of machine learning operations deteriorates
Solution Approach 1:
The patent implements preliminary action by pre-establishing associations between environment data and learning data before machine learning operations are performed. The base station or first user equipment associates environment data indicating environmental state with learning data in advance, enabling accurate machine learning operations without adding processing delay during the actual learning process.
3Adaptability or versatility
If environment data is associated with learning data, then the suitability of learning data for specific environments is improved, but the data processing complexity increases
Solution Approach 1:
The patent uses environment data as an intermediary that bridges the gap between general learning data and specific user environments. By associating environment data with learning data, the system determines suitability without requiring complex processing during machine learning operations, thus improving adaptability while managing data processing complexity through structured association rather than complex computation.
Data Source
AI summary
Provided is a communication method in a mobile communication system including a first user equipment, a second user equipment, and a network node capable of communicating with the first user equipment and the second user equipment, the mobile communication system being capable of deriving a first learned model using first learning data and deriving a second learned model using second learning data. The communication method includes associating, by any of the network node and the first user equipment, environment data indicating an environmental state of the first user equipment with first learning data.