Communication Device Dataset Metadata for Wireless Model Adaptation
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Solution Overview
Problem
The challenge in ML/AI-based wireless communication systems is the inefficient and incorrect utilization of acquired wireless communication 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, such as spatial, type, environment, and temporal features, enabling correct and efficient utilization of the dataset for model training and adaptation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If wireless communication datasets are collected without recording key characteristics, then data collection is simple and fast, but the datasets cannot be correctly and efficiently utilized for model training
Solution Approach 1:
The patent applies preliminary action by collecting and recording dataset characteristics (spatial, temporal, environmental information) during the data collection phase itself, rather than attempting to add this information later. The communication device automatically captures and stores these characteristics alongside the raw data, enabling correct and efficient utilization of the datasets for model training without requiring additional post-processing steps.
2Measurement precision
If dataset characteristics are recorded and stored, then model training accuracy is improved, but system complexity increases
Solution Approach 1:
The patent merges the data collection function with the characteristic recording function into a single integrated process. The communication device simultaneously captures raw wireless communication data and metadata characteristics (spatial coordinates, time stamps, environmental parameters) without requiring separate complex systems. This unified approach improves model training accuracy while avoiding the need for additional complex infrastructure.
Solution Approach 2:
The communication device performs self-service by automatically capturing and recording its own operational characteristics and environmental context during data collection. The device uses its built-in sensors and processing capabilities to generate and store dataset characteristics without requiring external assistance or complex additional equipment, thereby improving measurement precision while keeping system complexity manageable.
3Adaptability or versatility
If assistance information is provided about dataset characteristics, then model adaptation to specific scenarios is enabled, but information transmission requirements increase
Solution Approach 1:
The patent extracts only the essential characteristic information from the complete dataset context and transmits this condensed assistance information (spatial, temporal, environmental features) to the target device. By separating and transmitting only the critical metadata rather than the entire raw dataset, the system enables model adaptation to specific scenarios while minimizing information transmission overhead and avoiding data redundancy.
Data Source
AI summary
Provided are a communication method and a communication device. The communication method includes: a first device acquires first auxiliary information, the first auxiliary information being used to indicate a feature of a first data set.