Conducting GSM Network Performance Analysis and Reporting
1. Define Objectives and KPIs
A. Objectives:
Begin by clearly defining the objectives of your performance analysis. Common objectives include:
Identifying and resolving network issues:
Detect and address issues such as dropped calls, network congestion, and poor signal quality.
Enhancing network coverage and capacity:
Ensure that the network covers all intended areas adequately and has sufficient capacity to handle peak traffic loads.
Improving service quality:
Focus on improving user experience by minimizing call drops, improving call quality, and ensuring seamless data services.
Optimizing resource utilization:
Ensure that network resources such as spectrum, equipment, and personnel are used efficiently to maximize performance and minimize costs.
B. Key Performance Indicators (KPIs):
KPIs are critical metrics used to evaluate the performance of the GSM network.
Typical KPIs include:
Call Setup Success Rate (CSSR):
The percentage of call attempts that successfully connect to the network.
Drop Call Rate (DCR):
The percentage of calls that are unexpectedly terminated by the network.
Handover Success Rate (HSR):
The percentage of successful handovers between cells during a call.
Traffic Channel (TCH) Congestion Rate:
The percentage of time the network experiences congestion on the traffic channels.
Paging Success Rate:
The percentage of successful paging attempts, which indicates the network’s ability to reach users.
Signal Strength and Quality (RSSI and RxQual):
Measurements of the signal strength and quality received by the mobile device.
Data Throughput:
The rate at which data is successfully transferred over the network.
2. Data Collection
A. Network Management System (NMS):
Most GSM networks are managed by sophisticated NMS platforms that collect performance data from various network elements, including Base Transceiver Stations (BTS), Base Station Controllers (BSC), and Mobile Switching Centers (MSC). Ensure that your NMS is properly configured to collect and store relevant performance data.
B. Drive Testing:
Conduct drive tests to gather real-world data on network performance from a user’s perspective. This involves using specialized equipment to measure signal strength, quality, and other parameters while moving through different geographic areas.
Example:
Drive testing in urban areas with high-rise buildings can reveal issues related to signal reflection and multipath propagation, while testing in rural areas can help identify coverage gaps.
C. Subscriber Feedback:
Collect feedback from subscribers regarding their experience with the network. This can provide valuable insights into issues that might not be captured by technical measurements alone.
Example:
Implementing customer surveys or using mobile apps that allow users to report issues directly can help gather qualitative data on user experiences.
3. Data Processing and Analysis
A. Data Cleaning:
Ensure the collected data is clean and free from errors. This may involve filtering out anomalies, duplicates, and irrelevant data points.
Example:
Remove data points that are clearly erroneous, such as signal strength readings that are physically impossible given the network layout.
B. Data Aggregation:
Aggregate the data at various levels (e.g., hourly, daily, weekly) to identify patterns and trends. This step is crucial for spotting long-term issues and performance degradation.
Example:
Weekly aggregation can help identify trends in network usage and performance that might be missed in daily data.
C. Statistical Analysis:
Perform statistical analysis to understand the distribution of KPIs and identify outliers. Techniques such as mean, median, standard deviation, and variance can help in summarizing the data.
Example:
Use histograms to visualize the distribution of call drop rates across different cells and identify areas with unusually high drop rates.
D. Root Cause Analysis:
Identify the root causes of performance issues. This may involve:
Analyzing network logs:
Detect anomalies such as sudden spikes in call drops or handover failures.
Investigating specific geographic areas:
Focus on areas with poor performance to identify coverage gaps or interference sources.
Examining the performance of individual network elements:
Analyze the performance of BTS, BSC, and MSC to pinpoint malfunctioning equipment or configuration issues.
Example:
If a particular cell has a high call drop rate, investigate the cell’s configuration, neighboring cells, and recent changes to identify potential causes.
4. Performance Optimization
A. Parameter Tuning:
Adjust network parameters to optimize performance. This can include changes to power levels, handover thresholds, frequency allocation, and more.
Example:
Adjusting the power levels of BTS can help balance the load between cells and reduce congestion.
B. Capacity Planning:
Ensure that the network has sufficient capacity to handle current and future traffic loads. This may involve upgrading hardware, adding new BTS sites, or reallocating resources.
Example:
Conduct a traffic analysis to predict future growth and plan for additional capacity where needed.
C. Fault Management:
Implement robust fault management practices to quickly detect and resolve network issues. This includes automated alarms, real-time monitoring, and efficient incident response processes.
Example:
Set up automated alerts for KPIs that exceed predefined thresholds, enabling rapid response to potential issues.
5. Reporting
A. Report Structure:
Structure your report to clearly present the findings and recommendations. A typical report might include:
Executive Summary:
A high-level overview of the report’s key findings and recommendations.
Introduction and Objectives:
A brief introduction to the report and the objectives of the performance analysis.
Methodology:
A detailed description of the data collection and analysis methods used.
Data Collection and Analysis:
A presentation of the collected data and the results of the analysis.
Key Findings:
A summary of the key findings, including any identified issues and their root causes.
Recommendations:
Specific recommendations for improving network performance based on the findings.
Conclusion:
A summary of the report and any final thoughts or next steps.
B. Visualization:
Use visual aids such as graphs, charts, and maps to effectively communicate the performance data. Visualization helps in quickly identifying trends, patterns, and outliers.
Example:
Heatmaps can be used to show signal strength across different geographic areas, highlighting coverage gaps.
C. Audience-Specific Reports:
Tailor the reports to different audiences. For instance, a technical report might include detailed analysis and technical jargon, while an executive summary should focus on high-level insights and business implications.
Example:
For senior management, focus on key metrics and their impact on business goals, while providing technical staff with detailed data and specific recommendations for action.
6. Continuous Improvement
A. Feedback Loop:
Establish a feedback loop to continuously improve the analysis and reporting process. Incorporate feedback from stakeholders and learn from past analyses to refine your approach.
Example:
After each reporting cycle, gather feedback from stakeholders on the report’s usefulness and clarity, and adjust future reports accordingly.
B. Regular Monitoring:
Implement regular monitoring and reporting to ensure ongoing network performance optimization. This can involve automated reporting tools and dashboards for real-time performance tracking.
Example:
Use a network operations center (NOC) to continuously monitor network performance and generate real-time alerts for any issues that arise.
7.Tools and Technologies
A. Performance Management Systems:
Use advanced performance management systems that integrate data collection, analysis, and reporting functionalities. Examples include Ericsson’s OSS (Operations Support System) and Nokia’s NetAct.
Example:
These systems can automate the collection and analysis of performance data, reducing the need for manual intervention and enabling faster response to issues.
B. Drive Test Tools:
Employ specialized drive test tools such as TEMS Investigation, Nemo Outdoor, or Rohde & Schwarz ROMES for comprehensive field measurements.
Example:
These tools can provide detailed measurements of signal strength, quality, and other parameters in real-world conditions, helping to identify coverage gaps and other issues.
C. Data Analytics Platforms:
Leverage data analytics platforms like Tableau, Power BI, or custom-built solutions for in-depth analysis and visualization.
Example:
Use these platforms to create interactive dashboards that allow stakeholders to explore performance data and identify trends and issues.
8.Case Study: Real-World Application
A. Problem Identification:
A telecom operator observed a high drop call rate in a specific urban area. Initial data suggested poor signal quality and high interference levels.
B. Data Collection and Analysis:
Drive tests and NMS data collection revealed that several BTS sites in the area were experiencing high congestion and interference from nearby buildings.
c. Optimization Measures:
The operator implemented the following measures:
- Adjusted antenna tilts and power levels.
- Introduced additional BTS sites to reduce congestion.
- Conducted a frequency re-planning to minimize interference.
D. Outcome:
Post-optimization analysis showed a significant reduction in the drop call rate and improved overall network performance.
Conclusion
Conducting GSM network performance analysis and reporting is a complex but essential process for maintaining a high-quality mobile network. By following a structured approach that includes defining objectives, collecting and analyzing data, optimizing performance, and generating detailed reports, telecom operators can ensure their networks meet the demands of their subscribers. Continuous improvement and leveraging advanced tools and technologies further enhance the effectiveness of this process, leading to a more reliable and efficient GSM network.
In summary, the ability to systematically analyze and report on GSM network performance not only helps in maintaining service quality but also provides a strategic advantage in a highly competitive market. By focusing on detailed data analysis, proactive optimization, and clear reporting, telecom operators can significantly enhance their operational efficiency and customer satisfaction.