Reference AI Model Management for Wireless Communication Deployment
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Solution Overview
Problem
The challenge of managing artificial intelligence models in wireless communication networks is significant due to varying performance, complexity, and size, leading to inefficiencies and difficulties in deployment and management.
Innovation Solution
A reference model is defined to determine target models for specific communication processes, with partial model parameters or structures defined in the reference model, enabling efficient management and deployment without configuring multiple AI models.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple AI models are configured for different communication processes, then communication performance can be optimized, but model management complexity increases significantly
Solution Approach 1:
The patent applies universality by creating a reference model that serves multiple functions across different communication processes. Instead of configuring separate AI models for each communication scenario, a single reference model is established that can be adapted and applied to various communication processes, thereby optimizing performance while reducing model management complexity.
Solution Approach 2:
The patent segments the model management approach by separating the reference model (defined in the network device) from the target models (applied in communication devices). This segmentation allows the reference model to be maintained centrally while enabling flexible deployment of specific target models for different communication processes, reducing overall system complexity.
2Productivity
If AI models are frequently updated and managed in wireless networks, then communication efficiency improves, but signaling overhead increases
Solution Approach 1:
The patent extracts the model definition and management functions from individual communication devices and centralizes them in the network device. By taking out the burden of model management from communication devices and consolidating it in the network device, the system achieves better communication efficiency while reducing signaling overhead associated with frequent model updates.
3Adaptability or versatility
If different AI models are deployed for various communication scenarios, then system adaptability improves, but deployment difficulty increases
Solution Approach 1:
The patent applies preliminary action by pre-defining a reference model in the network device that encompasses multiple communication scenarios. This preliminary establishment of a comprehensive reference model enables the system to adapt to different communication scenarios without requiring complex deployment procedures for each specific model, thereby improving adaptability while simplifying deployment.
Data Source
AI summary
Provided are a model management method and apparatus, and a communication device. The model management method 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.