Wireless Model Identification Using Public and Local AI IDs
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Solution Overview
Problem
The increasing complexity and variability in wireless communication systems due to the use of multiple AI models for different problems, entities, environments, and accuracy requirements pose challenges in effectively instructing these models.
Innovation Solution
A method for wireless communication that involves determining and transmitting first information, such as a public or local identity associated with a model, to facilitate model identification and deployment in a communication system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple AI models are used for different problems and execution entities, then the accuracy of results is improved, but the complexity of instructing and managing models increases
Solution Approach 1:
The patent segments model identification into two distinct parts: public identity (shared across multiple execution entities) and local identity (specific to individual execution entities). This segmentation allows the system to manage multiple AI models efficiently by separating common identification information from entity-specific information, thereby reducing the overall complexity of model instruction while maintaining the ability to provide accurate results for different problems and entities
Solution Approach 2:
The patent introduces a new dimensional structure for model identification by adding the local identity dimension to the existing public identity dimension. This creates a two-dimensional identification space that enables precise model specification across multiple execution entities without linearly increasing management complexity. The dual-identity approach adds a structural dimension that organizes model references more efficiently
2Adaptability or versatility
If different models are deployed for the same problem across different execution entities, then the adaptability of the system is improved, but the difficulty of model management increases
Solution Approach 1:
The public identity component serves as a universal identifier that can be shared across multiple execution entities and models. This universal element provides a common reference point that simplifies model management while allowing each execution entity to have its own local identity. The combination enables the system to maintain adaptability for different deployment scenarios while reducing management difficulty through the standardized public identity framework
3Measurement precision
If detailed model identification information is transmitted, then the precision of model indication is improved, but the communication overhead increases
Solution Approach 1:
The patent extracts model identification information into two separate components: public identity and local identity. This extraction allows the system to transmit only the necessary combination of these identities rather than transmitting complete, redundant model specification data. By separating the identification information, the system achieves precise model indication while minimizing communication overhead, as execution entities can use the public identity (which may be pre-shared or efficiently transmitted) combined with the compact local identity to uniquely identify models
Data Source
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AI summary
Provided in the present application are wireless communication methods and communication devices. A method comprises: a first device determining first information, the first information comprising one or more of the following: a first public identifier associated with a first model used for wireless communication, and a first local identifier associated with the first model and/or the first public identifier. In the embodiments of the present application, the first device can determine the first information used for indicating the first model, thus facilitating indication of the first model in wireless communication systems.