Telefonaktiebolaget lm ericsson (publ) (20240098569). DEVICES, METHODS, AND SYSTEMS FOR PREDICTING RADIO ACCESS NETWORK PERFORMANCE simplified abstract
Contents
- 1 DEVICES, METHODS, AND SYSTEMS FOR PREDICTING RADIO ACCESS NETWORK PERFORMANCE
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 DEVICES, METHODS, AND SYSTEMS FOR PREDICTING RADIO ACCESS NETWORK PERFORMANCE - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 Original Abstract Submitted
DEVICES, METHODS, AND SYSTEMS FOR PREDICTING RADIO ACCESS NETWORK PERFORMANCE
Organization Name
telefonaktiebolaget lm ericsson (publ)
Inventor(s)
Samara Keshavarz Hedayati of Stockholm (SE)
Rerngvit Yanggratoke of Järfälla (SE)
[[:Category:Mattias Lidstr�m of Stockholm (SE)|Mattias Lidstr�m of Stockholm (SE)]][[Category:Mattias Lidstr�m of Stockholm (SE)]]
Marius Sorin Sirbu of Åkersberga (SE)
DEVICES, METHODS, AND SYSTEMS FOR PREDICTING RADIO ACCESS NETWORK PERFORMANCE - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240098569 titled 'DEVICES, METHODS, AND SYSTEMS FOR PREDICTING RADIO ACCESS NETWORK PERFORMANCE
Simplified Explanation
The abstract of the patent application describes methods, devices, and a system for predicting radio access network performance. A device is used to train a prediction model by obtaining information associated with network elements, determining tags based on network environment properties, associating clusters with network elements based on tags, determining performance indicator values for clusters, creating a training set, and training the prediction model using the training set.
- The device obtains information associated with network elements.
- Tags are determined based on network environment properties of the network elements.
- Clusters are associated with network elements based on the tags.
- Performance indicator values are determined for clusters.
- A training set is created comprising the performance indicator values of clusters.
- The prediction model is trained using the training set.
Potential Applications
This technology can be applied in the telecommunications industry to predict and optimize radio access network performance, leading to improved network efficiency and user experience.
Problems Solved
This technology solves the problem of accurately predicting radio access network performance, allowing for proactive maintenance and optimization of network elements.
Benefits
The benefits of this technology include improved network performance, reduced downtime, enhanced user experience, and cost savings through efficient network management.
Potential Commercial Applications
A potential commercial application of this technology could be in the development of network management software for telecom companies, offering predictive analytics for radio access network performance optimization.
Possible Prior Art
One possible prior art in this field could be predictive analytics software used in other industries for performance optimization of various systems and networks.
What are the specific network environment properties used to determine tags for network elements in this technology?
The specific network environment properties used to determine tags for network elements in this technology are not explicitly mentioned in the abstract. Further details may be provided in the full patent application document.
How does the prediction model trained by the device improve over time?
The abstract does not provide specific information on how the prediction model trained by the device improves over time. It would be beneficial to explore the training mechanisms and algorithms used to continuously enhance the prediction accuracy of the model.
Original Abstract Submitted
methods, devices, and a system for prediction of radio access network performance. a device for training a prediction model for predicting radio access network performance obtains information associated with at least one network element; determines a tag for the at least one network element, wherein the tag is based on a network environment property of the at least one network element; and determines, based on the tag, a cluster to be associated with the at least one network element. the device determines a performance indicator value for the at least one cluster, creates a training set comprising the performance indicator value of at least one cluster; and trains a prediction model using the training set. the prediction model trained by the device can be used by a device for prediction of radio access network performance.
