18707254. MACHINE LEARNING ASSISTED USER PRIORITIZATION METHOD FOR ASYNCHRONOUS RESOURCE ALLOCATION PROBLEMS simplified abstract (Telefonaktiebolaget LM Ericsson (publ))
Contents
MACHINE LEARNING ASSISTED USER PRIORITIZATION METHOD FOR ASYNCHRONOUS RESOURCE ALLOCATION PROBLEMS
Organization Name
Telefonaktiebolaget LM Ericsson (publ)
Inventor(s)
Peiliang Chang of Åkersberga (SE)
Akram Bin Sediq of Kanata (CA)
MACHINE LEARNING ASSISTED USER PRIORITIZATION METHOD FOR ASYNCHRONOUS RESOURCE ALLOCATION PROBLEMS - A simplified explanation of the abstract
This abstract first appeared for US patent application 18707254 titled 'MACHINE LEARNING ASSISTED USER PRIORITIZATION METHOD FOR ASYNCHRONOUS RESOURCE ALLOCATION PROBLEMS
The abstract of this patent application describes a method performed in a network node to allocate resources to a user equipment based on estimated data amount and resource utilization rate.
- Obtaining estimated data amount of a user equipment (UE) and a resource utilization rate.
- Obtaining a percentile R of the estimated data amount based on a data amount distribution table.
- Comparing the percentile R to the resource utilization rate.
- Allocating a resource to the UE if the percentile R is higher than the resource utilization rate.
Potential Applications: This technology could be applied in telecommunications networks to efficiently allocate resources to user equipment based on data usage patterns.
Problems Solved: This technology addresses the challenge of optimizing resource allocation in networks to meet the demands of user equipment effectively.
Benefits: - Improved resource utilization in networks - Enhanced user experience through optimized resource allocation - Efficient management of network resources
Commercial Applications: This technology could be valuable for telecommunications companies looking to enhance network performance and user satisfaction through intelligent resource allocation strategies.
Questions about the Technology: 1. How does this technology improve resource allocation in networks? 2. What are the key factors considered when allocating resources to user equipment?
Original Abstract Submitted
A network node, computer program, computer program product, and a method performed in a network node includes obtaining an estimated data amount of a user equipment, UE, and a resource utilization rate. A percentile R of the estimated data amount is obtained based on a data amount distribution table. The percentile R is compared to the resource utilization rate. Responsive to the percentile R being higher than the resource utilization rate, a resource is allocated to the UE.
