Radio Resource Allocation Using Machine-Trained Functions
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Solution Overview
Problem
Current radio communication methods face inefficiencies in resource allocation and synchronization between disjoint radio nodes using the same channel, leading to increased control signaling overhead and reduced spectrum efficiency.
Innovation Solution
A method involving the collection and analysis of radio traffic data sets to train machine-trainable functions, allowing for the determination of utilization schemes and allocation of radio resources without a central granting procedure, enabling synchronized resource allocation and reduced overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a central granting procedure is used for resource allocation, then resource allocation control is improved, but control signaling overhead increases
Solution Approach 1:
The patent enables radio nodes to autonomously determine resource utilization schemes using machine-trained functions without requiring central granting procedures. Each node independently analyzes traffic data sets and determines its own resource allocation, eliminating the need for extensive control signaling between central controller and nodes.
Solution Approach 2:
The patent introduces machine-trained functions as intermediaries that process traffic data and generate resource utilization schemes. These trained functions act as mediators between raw traffic data and resource allocation decisions, enabling distributed nodes to make informed decisions without direct central control signaling.
2Productivity
If disjoint radio nodes use the same radio channel independently, then spectrum efficiency is improved, but synchronization between nodes deteriorates
Solution Approach 1:
The patent trains machine models at multiple radio nodes using identical or equivalent traffic data sets and training configurations, ensuring that all nodes operate at the same decision-making level. This equipotential approach ensures synchronized resource utilization schemes across disjoint nodes while maintaining independent spectrum usage.
Solution Approach 2:
The patent uses rectification indicators to detect and correct deviations in machine model parameters between nodes. When synchronization drift is detected, the system adjusts parameters such as training configuration, data collection settings, or model architecture to restore synchronization while maintaining efficient spectrum usage.
3Measurement precision
If machine learning models are trained with high accuracy requirements, then resource utilization scheme determination is improved, but training time and complexity increase
Solution Approach 1:
The patent implements iterative training where machine models are trained incrementally using available traffic data sets. Rather than requiring complete and perfect training data before deployment, the system uses partial training results and continuously refines models as more data becomes available, reducing initial training time while maintaining adequate accuracy.
Solution Approach 2:
The patent employs feedback mechanisms where rectification indicators monitor the synchronization and performance of trained models across nodes. This feedback enables the system to identify when retraining or parameter adjustment is needed, optimizing the balance between model accuracy and training time by only retraining when necessary.
Data Source
AI summary
A method for operating a first apparatus. The method includes: collecting at least one first radio traffic data set that is associated with a utilization of at least one radio channel; training a machine-trainable function based on the collected at least one first radio traffic data set; collecting at least one second radio traffic data set, which is associated with the utilization of the at least one radio channel, wherein the second traffic data set is different from the first data set; determining, using the machine-trained function, at least one utilization scheme associated with the at least one radio channel based on the at least one second radio traffic data set; allocating at least one radio resource on the at least one radio channel according to the determined utilization scheme; and transmitting data via the at least one allocated radio resource of the at least one radio channel.