Reference AI Model Management for Stable Wireless Communication
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Solution Overview
Problem
The variability in AI model designs, performance, and sizes across terminals complicates AI model management, affecting communication performance in wireless networks.
Innovation Solution
Implementing a reference model with defined model parameters or structures to manage target models, allowing efficient AI model management and improved communication performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If various AI model designs are used by terminals for the same communication process, then model performance and adaptability can be optimized, but model management complexity increases significantly
Solution Approach 1:
The patent establishes a universal reference model that can serve multiple communication processes and different terminal types. The reference model contains standardized parameter definitions and model structure templates that can be reused across various scenarios, allowing one model framework to fulfill multiple functions rather than requiring separate models for each communication process.
Solution Approach 2:
The patent manages AI model variability by controlling and standardizing model parameters through the reference model. Instead of allowing free variation of all parameters, the system defines which parameters can be adjusted and which must remain standardized, enabling adaptability within controlled boundaries that prevent management complexity from becoming unmanageable.
2Reliability
If AI models with varying performance and sizes are deployed, then communication performance can be optimized for different scenarios, but model management difficulty increases
Solution Approach 1:
The patent segments AI model management into two distinct layers: the reference model layer that defines standardized parameters and structures, and the target model layer that implements specific communication processes. This segmentation allows performance optimization at the target model level while maintaining manageable complexity at the reference model level, where standardization reduces management difficulty.
Solution Approach 2:
The reference model acts as an intermediary between model development and model deployment. It provides a standardized interface and parameter definition system that mediates between the need for varied performance characteristics in different scenarios and the need for simplified management operations, translating performance requirements into standardized model configurations.
3Productivity
If standardized reference models are implemented, then model management efficiency is improved, but model design flexibility may be reduced
Solution Approach 1:
The patent implements a dynamic model management system where the reference model provides standardized frameworks but allows configurable parameters and structures for target models. The system can dynamically adapt the level of standardization based on specific communication process requirements, maintaining management efficiency through standardization while preserving design flexibility where needed through configurable parameters.
Data Source
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AI summary
This application discloses a model management method and apparatus, and a communication device, and relates to the field of communication technologies. The model management method in embodiments of this application includes: performing, by a first communication device, model management on a reference model, where at least a part of model parameters or at least a part of model structures of a target model are defined in the reference model, and the target model is used by the first communication device for performing a predetermined communication process.