Automated Handover Optimization in Wireless Networks
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Solution Overview
Problem
Current wireless communication systems experience handover failures due to improperly configured or manually controlled handover parameters, leading to issues like premature or delayed handovers, and 'ping-ponging' between stations, which disrupt communication services.
Innovation Solution
Implementing an automated system that dynamically adjusts handover parameters such as time-to-trigger (TTT), Cell Individual Offsets (CIO), and other parameters based on real-time measurements to optimize handover timing and reduce failures, using a processor to execute instructions for monitoring and adjusting these parameters to ensure efficient handovers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If handover parameters are manually configured, then device complexity is reduced, but handover reliability deteriorates due to improper configuration
Solution Approach 1:
The system enables self-service by allowing the network to automatically monitor handover performance metrics and adjust handover parameters without manual intervention. The network entity continuously analyzes handover failure rates and dynamically optimizes parameters such as time-to-trigger and offset values, making the system self-configuring and self-optimizing.
Solution Approach 2:
The invention implements feedback mechanisms where the network monitors handover performance metrics including handover failure rates, call drop rates, and radio link failure rates. Based on this feedback, the system dynamically adjusts handover parameters to optimize performance, creating a closed-loop control system that continuously improves handover reliability.
2Reliability
If handover parameters are dynamically adjusted, then handover reliability improves, but device complexity increases due to automated monitoring and adjustment mechanisms
Solution Approach 1:
The network entity performs self-service by automatically monitoring handover performance and adjusting parameters without external intervention. The system autonomously collects performance data, analyzes trends, and modifies handover parameters to maintain optimal operation, reducing the need for complex external management systems.
Solution Approach 2:
The network entity performs multiple functions including performance monitoring, data analysis, parameter optimization, and handover control within a single integrated system. This multi-functional approach consolidates complexity into a centralized controller rather than distributing it across multiple separate systems.
3Reliability
If handover timing is optimized, then handover failures are reduced, but loss of time occurs during parameter measurement and analysis
Solution Approach 1:
The system implements continuous monitoring and analysis of handover performance metrics without interruption to normal handover operations. Performance data is collected continuously in the background, allowing the system to maintain optimal handover parameters over time without requiring periodic system stops or interruptions to communication services.
Solution Approach 2:
The system performs preliminary analysis of performance trends and proactively adjusts handover parameters before failures occur. By continuously monitoring metrics and predicting potential issues, the system can pre-optimize parameters to prevent handover failures rather than reacting after problems arise, reducing the effective time loss.
4Measurement precision
If more handover parameters are monitored, then handover optimization accuracy improves, but device complexity increases due to extensive measurement requirements
Solution Approach 1:
The network entity serves as a universal monitoring platform that handles multiple measurement functions including signal strength measurement, quality assessment, failure rate tracking, and performance analysis within a single system. This consolidation reduces the complexity that would arise from having separate monitoring systems for each parameter.
Solution Approach 2:
The system merges multiple measurement and analysis functions into an integrated process. Performance metrics for different parameters are collected, correlated, and analyzed together to identify root causes of handover failures and determine optimal parameter adjustments, reducing the complexity of managing separate measurement systems.
Data Source
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AI summary
A method for wireless communications is provided. The method includes determining a set of handover parameters that facilitate a handover between cells in a wireless network and analyzing the set of handover parameters. The method includes dynamically adjusting the parameters to mitigate handover failures between the cells.