Functionality Selection Assistance for AI/ML Network Nodes
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Solution Overview
Problem
Existing mobile devices and networks face inefficiencies in functionality compatibility, leading to latency and poor performance due to differing device capabilities and network-supported functionalities.
Innovation Solution
The implementation of an apparatus in User Equipment (UE) that receives requests for supported functionalities and functionality selection assistance information from network nodes, identifies supported functionalities, determines functionality selection assistance information, and provides indications to network nodes, allowing for the selection of optimal functionalities based on UE preferences and resource availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If devices support multiple functionalities to improve versatility, then adaptability improves, but device complexity increases
Solution Approach 1:
The UE performs preliminary actions by proactively identifying and reporting its supported functionalities and determining functionality selection assistance information before the network node needs to make a selection. This allows the network to make informed decisions without requiring complex real-time analysis of device capabilities.
Solution Approach 2:
The functionality selection assistance information acts as an intermediary that bridges the gap between device capabilities and network-supported functionalities. Instead of directly comparing complex device specifications with network capabilities, the assistance information provides a simplified intermediate representation that facilitates efficient matching.
2Device complexity
If the network selects functionalities without assistance information, then device complexity is reduced, but loss of information occurs regarding optimal functionality selection
Solution Approach 1:
The patent extracts the essential functionality selection assistance information from the complex device capabilities and transmits only this distilled information to the network. This separates the critical selection criteria from the full device specification, reducing information loss while minimizing data transmission requirements.
3Measurement precision
If functionality selection is delayed to gather more information, then measurement precision improves, but loss of time occurs
Solution Approach 1:
The UE performs the functionality identification and assistance information determination in advance, before the network node needs to make the final selection. This preliminary action ensures that when the network receives the information, it can immediately make an informed decision without requiring additional time for analysis or information gathering.
Data Source
AI summary
Methods, apparatuses, and computer program products provide means for functionality selection assistance to determine selection of a preferred functionality for an Artificial Intelligence/Machine Learning model feature. An example method includes: receiving a request for supported functionalities from a network node; identifying the supported functionalities; determining functionality selection assistance information; and providing an indication of the supported functionalities and the functionality selection assistance information to the network node. A method can optionally include receiving an indication of a selected functionality of the supported functionalities based, at least in part, on the functionality selection assistance information; and employing the selected functionality to support a feature.