NETWORK OPTIMIZATION SOLUTION
Harnessing AI algorithms to improve the efficiency and performance of networks
CSPs encounter challenges in managing diverse technologies (2G to 5G), intricate network topologies, dynamic traffic fluctuations, and swift adaptation to evolving technology for efficient optimization.
Managing diverse technologies and vendors within a network, poses challenges in maintaining seamless integration and optimizing performance across different generations of networks.
Multi-RAT and multi-vendor networks
Fluctuations in network traffic demand require dynamic optimization approaches to handle varying loads effectively and prevent congestion or service degradation during peak usage
Traffic balancing strategies
In a network with hundreds of thousands of elements, the identification and resolution of issues become highly complex without automation.
Root-cause analysis and resolution
Traditional tools rely on cell-ID analysis, posing significant challenges when indoor analysis is necessary.
Analysis of specific areas: points of interests, roads, etc.
When engineers need to analyze an area, they often find themselves using tools from various providers, resulting in a time-consuming and inefficient process.
Multi data sources analysis implies using different tools
Legacy solutions utilize multiple servers, resulting in higher costs.
Scalable software solution not cloud native
Kenmei proposes a cloud-based network optimization solution, integrating multi-domain data sources and automating the analysis and resolution of network issues.
Obtain automatic root-causes for planning, optimization, and configuration.
ROOT CAUSE ANALYSIS
Correlation between OSS and Geo data sources to improve network performance analysis.
Network performance comparison between different operators.
Detection of network congestion, both RAN and TRX, and recommendations to alliviate the issue.
CAPACITY & LOAD BALANCING ANALYSIS
Overlay of topology on top of multiple network measurements.
NETWORK TOPOLOGY ANALYSIS
Automated analysis of roads, streets, malls, hospital, airports, etc.
OPEN-DATA SEGMENTED ANALYTICS
Network optimization automation for CSPs brings economic benefits by reducing operational costs, minimizing downtime, optimizing resource usage, and enhancing service quality, resulting in overall cost efficiency and competitiveness.
Automation streamlines routine network optimization tasks, reducing the need for manual intervention. This efficiency leads to lower labor costs and increased productivity among network engineering teams.
Boost teams productivity with automation
OSS provides a cell-centric perspective, while hotspot analysis necessitates a more granular examination of areas spanning a few meters.
Improve visibility of specific hotspots and VIP areas
Instead of relying solely on drive tests for troubleshooting, automated systems can analyze extensive datasets to predict and prevent potential issues, reducing the need for reactive measures.
Reduce the investment in field measurements
Faster issue detection and resolution with root cause analysis algorithms involves promptly identifying and addressing network problems by pinpointing their underlying causes through advanced automated analytical processes.