AI Engine Corrects Wireless Handover Errors
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Solution Overview
Problem
Handover errors in wireless communication networks, such as LTE, 4G, and 5G, occur frequently due to configuration issues between base stations from different manufacturers or software versions, making it impractical for human resources to correct all errors efficiently, leading to service disruptions.
Innovation Solution
A method using an artificial intelligence engine to proactively detect handover errors and implement solutions, including machine learning algorithms, to correct configuration issues in base station configurations and neighbor relation tables, utilizing databases of past errors to identify and implement solutions automatically or with human intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human resources are used to correct handover errors manually, then solution accuracy may be maintained, but productivity and response time deteriorate significantly
Solution Approach 1:
The system enables self-service by allowing the AI engine to automatically detect handover errors, determine solutions, and implement corrections without requiring manual human intervention for each error case, thereby maintaining accuracy while significantly improving productivity
Solution Approach 2:
The system implements feedback mechanisms where the AI engine learns from past error patterns and solutions stored in databases, continuously improving its accuracy through feedback loops that analyze successful corrections and update its algorithms
2Reliability
If manual monitoring and correction of handover errors is performed, then solution quality may be maintained, but loss of time increases
Solution Approach 1:
The system performs preliminary actions by proactively detecting handover errors before they cause service disruptions and by pre-loading solution databases with known error patterns, enabling faster response time while maintaining solution quality
Solution Approach 2:
The AI engine operates continuously to monitor network conditions, detect errors, and implement corrections without interruption, eliminating the downtime and delays associated with manual monitoring processes
3Reliability
If comprehensive error detection and correction systems are implemented, then network reliability improves, but device complexity increases
Solution Approach 1:
The system introduces an intermediary AI engine that acts as a mediator between network monitoring components and correction mechanisms, simplifying the overall architecture by consolidating detection, analysis, and correction functions in a single intelligent layer
Data Source
AI summary
Proactively detecting one or more handover error in a communication link between base stations [14y, 14z] in a wireless communication network. A method may include determining at least one possible solution to the one or more handover error using an artificial intelligence engine 76. A method may include implementing the at least one possible solution to correct the one or more handover error. The artificial intelligence engine 76 may include an artificial intelligence algorithm, a machine learning algorithm, a deep learning algorithm, a neural network algorithm; and/or big data analysis algorithm. The artificial intelligence engine 76 may utilize at least one database [92, 94, 96] including a plurality of solutions. The plurality of solutions may include solutions to errors in communication networks that occurred in the past. The artificial intelligence engine 76 may successively implement each of the possible solutions until the one ore more handover error is corrected.