Wireless AI Model Activation for Multi-Function Throughput
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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, thereby improving system performance and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If independent models are used for each functionality, then each functionality can be implemented independently, but system throughput and spectral efficiency deteriorate
Solution Approach 1:
The patent merges multiple independent AI/ML models into a unified joint model that handles multiple functionalities simultaneously. The network device receives joint indication information and determines activation status of the unified model, enabling coordinated optimization of system throughput and spectral efficiency across multiple functionalities rather than treating them independently.
Solution Approach 2:
The patent implements a universal AI/ML model architecture that can perform multiple functionalities through a single model. The joint indication information mechanism allows the network device to activate or deactivate the unified model for multiple functionalities (such as channel estimation, interference cancellation, and signal detection) simultaneously, achieving multi-functionality with optimized system performance.
2Device complexity
If independent models are used for each functionality, then model management is simpler for individual functions, but spectral efficiency deteriorates
Solution Approach 1:
The patent combines multiple functionality-specific models into a single joint AI/ML model. The network device manages this unified model through joint indication information, which simultaneously controls activation status for multiple functionalities. This merging approach improves spectral efficiency by enabling coordinated resource allocation and model optimization across all functionalities, despite requiring centralized management of the joint model.
3Manufacturing precision
If AI capability is activated for multiple functionalities independently, then each functionality can be optimized individually, but model training efficiency deteriorates
Solution Approach 1:
The patent merges the training process of multiple functionality-specific models into a single joint model training operation. By receiving joint indication information and activating a unified AI capability for multiple functionalities simultaneously, the system trains one comprehensive model that captures correlations between different functionalities, significantly improving model training efficiency while maintaining optimization precision through the joint learning framework.
Data Source
AI summary
Provided are a wireless communication method, a terminal device, and a network device, which are beneficial for ensuring the performance of a model. The method includes: 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.