ML Function Time-Window Synchronization Between Communication Nodes
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Solution Overview
Problem
Existing communication systems lack efficient methods for synchronizing machine learning-based functions between communication nodes and effectively managing performance metrics and actions within defined time windows, leading to inefficiencies and inconsistencies in wireless communication.
Innovation Solution
Implementing a method and apparatus for synchronizing a common reference timing and configuring a machine learning-based function between communication nodes, with mechanisms for measuring performance metrics, assigning time identifications, and providing measured information within specified time windows, allowing for coordinated execution and action management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If independent machine learning-based functions are implemented at each communication node, then each node can autonomously optimize its performance, but radio interference and quality of service degradation occur due to lack of coordination
Solution Approach 1:
The patent merges the independent machine learning functions at different communication nodes by introducing a coordinating entity that collects performance metrics from multiple nodes and generates coordinated actions. This combining approach allows each node to maintain its autonomous optimization capability while ensuring overall system coordination through shared information and synchronized actions, thereby preventing radio interference and quality of service degradation.
2Device complexity
If machine learning-based functions operate independently without synchronized timing, then implementation complexity is reduced, but learning accuracy and performance optimization deteriorate
Solution Approach 1:
The patent applies preliminary action by establishing a common reference timing and pre-defining time windows for performance metric collection and action execution before the machine learning process begins. This pre-synchronization ensures that all communication nodes operate on the same time basis, enabling accurate comparison and coordination of learned behaviors without requiring complex real-time synchronization mechanisms during operation.
3Ease of operation
If performance metrics are collected without time window synchronization, then data collection is simpler, but the ability to correlate actions with their effects deteriorates
Solution Approach 1:
The patent implements feedback by collecting performance metrics within synchronized time windows and using these metrics to evaluate the effects of previously executed actions. The coordinating entity aggregates feedback from multiple communication nodes, correlates it with the actions taken during the same time window, and uses this information to generate improved actions for the next time window, thereby maintaining accurate action-effect correlation while keeping data collection systematic and manageable.
Data Source
AI summary
An apparatus of a first communication node is provide that includes: means for synchronising a common reference timing with a second communication node; means for obtaining an indication of a time window that specifies a period of time between first and second time instances; and means for configuring a machine learning-based function at the first communication node, wherein the configuration of the machine learning-based function is common between the first and second communication nodes. The apparatus further includes means for executing the machine learning-based function; and means for obtaining information by measuring a performance metric, for the machine learning-based function, during the time window. The apparatus further includes means for assigning a time identification to the measured information during the time window, wherein the time identification is associated with the common reference timing; and means for providing, to the second communication node, the measured information according to the time identification.