Wireless AI Model Activation for Multi-Function Network Throughput
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing communication systems face challenges in managing AI/ML models for multiple functionalities, leading to suboptimal performance and inefficiencies in system throughput and spectral efficiency.
Innovation Solution
A method for wireless communication that involves a terminal device and network device to manage activation information of AI capabilities or models for multiple functionalities, allowing for joint indication of activation status using target information, enabling better KPI performance and improved model training and data set collection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If separate models are used for each functionality, then each functionality can be independently optimized, but the overall system performance and spectral efficiency deteriorate
Solution Approach 1:
The patent combines multiple separate functionality models into a unified AI model that handles multiple functionalities simultaneously. This merging approach allows the system to achieve better overall performance and spectral efficiency while maintaining the ability to perform individual functionalities through the integrated model.
Solution Approach 2:
The patent implements a universal AI model that can perform multiple functionalities through a single model structure. This multi-functional model is designed to handle various communication tasks simultaneously, improving system throughput and spectral efficiency compared to multiple separate models.
2Reliability
If multiple independent models are deployed for multiple functionalities, then each functionality can be optimized separately, but the complexity of model management increases
Solution Approach 1:
The patent merges multiple functionality-specific models into a single unified AI model, thereby reducing model management complexity. The unified model structure simplifies deployment, training, and maintenance while still enabling separate optimization of individual functionalities through the integrated architecture.
3Ease of manufacture
If separate models are used for each functionality, then model training can be performed independently, but the efficiency of model training and data set collection deteriorates
Solution Approach 1:
The patent combines data collection and training processes for multiple functionalities into a unified framework. This allows for more efficient data set collection that can be used across multiple functionalities simultaneously, improving training efficiency while maintaining the ability to train and optimize individual functionality components.
Data Source
Figure 1~3
Figure 4
Figure 5~7
AI summary
A wireless communication method, a terminal device, and a network device, which are beneficial for ensuring the performance of a model. The method comprises: a terminal device receiving target information sent by a network device, wherein the target information is used for determining activation information of artificial intelligence (AI) capabilities corresponding to a plurality of functions or activation information of models corresponding to the plurality of functions.