17838624. INTELLIGENT INFRASTRUCTURE MANAGEMENT IN A CLOUD RADIO ACCESS NETWORK simplified abstract (Dell Products L.P.)
INTELLIGENT INFRASTRUCTURE MANAGEMENT IN A CLOUD RADIO ACCESS NETWORK
Organization Name
Inventor(s)
Parminder Singh Sethi of Ludhiana (IN)
Nithish Kote of Bangalore (IN)
INTELLIGENT INFRASTRUCTURE MANAGEMENT IN A CLOUD RADIO ACCESS NETWORK - A simplified explanation of the abstract
This abstract first appeared for US patent application 17838624 titled 'INTELLIGENT INFRASTRUCTURE MANAGEMENT IN A CLOUD RADIO ACCESS NETWORK
Simplified Explanation
The patent application describes techniques for intelligent infrastructure management in a radio access network. It involves using machine learning models to analyze operational statistics of baseband units and predict future technical issues. Here is a simplified explanation of the patent application:
- The method obtains operational statistics of baseband units in a radio access network.
- A forecasted data set is generated using a machine learning model to predict future operational statistics of the baseband units.
- The forecasted data set is analyzed using another machine learning model to predict future technical issues.
- Based on the analysis, at least one corrective action is determined for the predicted future occurrence of the technical issue.
- The method then initiates the corrective action.
Potential Applications
This technology can be applied in various industries and scenarios where intelligent infrastructure management is crucial. Some potential applications include:
- Telecommunications: Optimizing the performance and maintenance of radio access networks.
- Internet of Things (IoT): Managing and monitoring large-scale IoT deployments efficiently.
- Smart Cities: Enhancing the management of infrastructure in urban environments.
- Industrial Automation: Improving the maintenance and reliability of industrial networks.
Problems Solved
The techniques described in the patent application address several problems in infrastructure management:
- Proactive Issue Detection: By analyzing operational statistics and predicting future technical issues, potential problems can be identified before they occur.
- Efficient Maintenance: The use of machine learning models enables the determination of corrective actions, allowing for timely and targeted maintenance.
- Enhanced Network Performance: By predicting and addressing technical issues, the overall performance and reliability of the network can be improved.
Benefits
The use of intelligent infrastructure management techniques outlined in the patent application offers several benefits:
- Cost Savings: Proactive issue detection and targeted maintenance can help reduce downtime and minimize costly repairs.
- Improved Efficiency: By automating the analysis and prediction process, resources can be allocated more efficiently, leading to optimized network performance.
- Enhanced Reliability: Predicting and addressing technical issues in advance improves the overall reliability and availability of the infrastructure.
- Scalability: The techniques can be applied to large-scale networks, making it suitable for various industries and deployments.
Original Abstract Submitted
Techniques are disclosed for intelligent infrastructure management in a radio access network. For example, a method obtains, from a plurality of baseband units of a radio access network, a plurality of data sets, wherein respective ones of the plurality of data sets correspond to operational statistics of respective ones of the plurality of baseband units. The method then generates a forecasted data set corresponding to one or more predicted operational statistics of each of the subset of baseband units, wherein the forecasted data set is generated using a first machine learning model. The method analyzes the forecasted data set to predict a future occurrence of a technical issue and to determine at least one corrective action for the predicted future occurrence of the technical issue, wherein the analysis is performed using a second machine learning model. The method then causes initiation of the at least one corrective action.
