Wireless Communication Dataset Metadata for Scenario-Adaptive Models
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Solution Overview
Problem
The challenge in ML/AI-based wireless communication systems is the inefficient utilization of acquired datasets due to the lack of recording key characteristics during data collection, making it difficult to construct refined models adapted to specific scenarios or environments.
Innovation Solution
A communication method and device that acquires and provides assistance information to indicate the characteristics of a dataset, enabling correct and efficient utilization by associating spatial, type, environment, transmission, and temporal features with the dataset.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dataset acquisition is performed without recording key characteristics, then data collection is simple and fast, but the dataset cannot be correctly and efficiently utilized for model construction
Solution Approach 1:
The patent applies preliminary action by acquiring assistance information about dataset characteristics (such as spatial, temporal, environmental features) during the data collection phase itself. This preliminary recording of metadata enables subsequent correct and efficient dataset utilization without requiring complex re-collection or processing later. The assistance information is prepared in advance to support model construction and adaptation.
2Loss of information
If assistance information is acquired and transmitted, then dataset characteristics are accurately recorded, but communication overhead and system complexity increase
Solution Approach 1:
The patent extracts only the essential assistance information (key characteristics of the dataset) from the complete data collection process. Rather than transmitting all raw data or excessive metadata, the system selectively extracts and transmits only the necessary characteristic information (such as spatial coordinates, time stamps, environmental conditions) that is sufficient for model construction and dataset utilization, thereby reducing communication overhead while preventing information loss.
3Adaptability or versatility
If detailed assistance information is recorded, then model adaptation to specific scenarios is enhanced, but data processing time and storage requirements increase
Solution Approach 1:
The patent applies local quality by recording specific characteristic information tailored to the requirements of different scenarios and models. Rather than uniformly recording all possible data attributes, the system selectively records assistance information that is locally relevant to each specific application scenario (such as spatial characteristics for positioning models, environmental characteristics for communication models), thereby enhancing model adaptability without proportionally increasing processing time and storage requirements.
Data Source
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AI summary
Provided are a communication method and a communication device. The communication method comprises: a first device acquires first auxiliary information, the first auxiliary information being used to indicate a feature of a first data set. In an embodiment of the present application, the first device can acquire the first auxiliary information, so that the first device can learn about the feature of the first data set according to the first auxiliary information, which thus helps ensure correct and efficient utilization of the first data set.