Cell Verification Using Neighbor Parameters and KPI Discrepancy Checks
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Solution Overview
Problem
Conventional manual verification methods for network elements such as macro cells, small cells, and bi-sector antennas are time-intensive, prone to human error, and lack consistency, leading to inefficient network deployment and increased operational costs.
Innovation Solution
A system and method that automates the analysis of Performance Management Key Performance Indicators (PM KPIs) to identify discrepancies in network elements, optimizing Remote Electrical Tilt (RET) and minimizing manual intervention, using advanced techniques to streamline verification and remotely adjust antenna tilt angles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual verification methods are used for network elements, then human operators can perform configuration and testing, but the process becomes time-intensive and labor-costly
Solution Approach 1:
The system performs self-verification by automatically comparing KPIs against predefined thresholds and detecting configuration issues without requiring manual intervention. The automated verification engine independently executes testing procedures and generates reports, eliminating the need for human operators to manually verify each network element.
Solution Approach 2:
The patent replaces manual mechanical verification processes with an automated computer-based system. The verification engine uses software algorithms to automatically collect KPI data, compare against thresholds, and detect issues, substituting human operational mechanics with automated digital processing.
2Reliability
If manual verification methods are used, then operators can perform configuration checks, but the process is prone to human error and lacks consistency
Solution Approach 1:
The system continuously monitors KPIs and provides automatic feedback when thresholds are exceeded or configuration issues are detected. The verification engine compares actual KPI values against predefined thresholds and immediately identifies deviations, providing consistent feedback mechanisms that eliminate human judgment variability.
Solution Approach 2:
The patent changes the verification approach from manual qualitative assessment to automated quantitative parameter comparison. By transforming verification into automated numerical threshold comparison, the system eliminates human error and ensures consistent, reproducible results across all network elements.
3Manufacturing precision
If manual verification is performed on each network element individually, then detailed configuration checks can be conducted, but the overall process slows down network deployment
Solution Approach 1:
The automated verification engine operates continuously and concurrently with network deployment activities. Instead of sequential manual verification, the system performs automated KPI collection and analysis continuously, enabling parallel processing of verification tasks alongside network installation and configuration activities.
Solution Approach 2:
The system performs preliminary automated verification checks immediately upon network element activation, before manual review is needed. By conducting automated KPI comparison and configuration validation as preliminary actions, the system ensures quality control is built-in from the start rather than added as a subsequent manual step.
Data Source
AI summary
The present invention discloses a method (600) for verification testing of cells in a network (106). The method (600) comprising identifying (602) at least one cell added to a database (210) of the network (106), identifying (604) a plurality of neighboring cells associated with the at least one cell, and obtaining (606) a set of parameters for the at least one cell and each of the plurality of neighboring cells from the database (210). The method (600) comprising determining (608) if the set of parameters meets a predefined criterion. When the set of parameters fail to meet the predefined criterion, performing following steps identifying (610), among the at least one cell and the plurality of neighboring cells, a first cell lacking a predefined set of configurations and modifying (612) a current set of configurations of the first cell based on the predefined set of configurations.