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Our premium Telecommunication client struggled with a high volume of Call Quality data which comprised of following parameters and further downstream processing using ML/AI to determine degradation of services and perform corrective actions.

 Quality of Service (QoS) parameters are critical metrics used in the telecommunications industry to measure and ensure the performance and reliability of communication services. These parameters help assess the overall user experience, network efficiency, and the level of service that a telecommunication network is delivering. Here are some key QoS parameters that are measured and monitored in the telecommunications industry:

1. Latency (Delay):

• Latency measures the time it takes for data packets to travel between the source and destination in a network.
• Low latency is crucial for real-time communication applications like voice and video calls.
• Measured in milliseconds (ms), lower latency indicates better network performance.

2. Jitter:

• Jitter refers to the variation in the delay of data packet arrival at the destination.
• High jitter can lead to disruptions in real-time applications, causing audio and video glitches.
• It is usually measured in milliseconds and should be minimized for smooth communication.

3. Packet Loss:

• Packet loss measures the percentage of data packets that do not reach their destination due to network congestion, errors, or other issues.
• Excessive packet loss can degrade the quality of voice and video calls and impact data transmission.
• Measured as a percentage, lower packet loss indicates better network reliability.

4. Throughput:

• Throughput represents the amount of data that can be transmitted over a network in a given period.
• Measured in bits per second (bps) or megabits per second (Mbps), higher throughput indicates a network's capacity to handle data traffic.

5. Bandwidth:

• Bandwidth refers to the maximum data capacity of a network connection.
• It determines the volume of data that can be transmitted at a given time.
• Insufficient bandwidth can lead to slow data transfer speeds and poor user experience.

6. Availability:

• Availability measures the percentage of time a network or service is operational and accessible to users.
• High availability is crucial to ensure uninterrupted communication services.

7. Call Setup Success Rate:

• For voice communication services, call setup success rate measures the percentage of successfully established calls out of the total attempted calls.
• It reflects the efficiency of call initiation processes and network reliability.

8. Call Drop Rate:

• Call drop rate indicates the percentage of ongoing calls that are prematurely terminated.
• High call drop rates can result from network congestion, handover failures, or other issues.

9. Handover Success Rate:

• Handover success rate measures the percentage of successful handovers (seamless transfer of an ongoing call or data session) between different network cells or technologies.
• Handover failures can lead to dropped calls or interruptions.

10. Mean Opinion Score (MOS):

• MOS is used to assess the overall quality of voice communication.
• It is determined through subjective user feedback and rates the call quality on a scale from 1 to 5, with 5 being excellent.

11. Video Quality Metrics:

• For video communication services, parameters like Video Quality Index (VQI), Video MOS (VMOS), and Structural Similarity Index (SSIM) are used to assess video quality and user experience.

12. Network Reliability and Redundancy:

• Measures of network reliability include Mean Time Between Failures (MTBF) and Mean Time to Repair/Recovery (MTTR).
• Redundancy measures, such as the availability of backup routes and failover mechanisms, help ensure service continuity.

Monitoring and optimizing these QoS parameters are essential to delivering high-quality telecommunication services that meet user expectations and provide a seamless communication experience. Telecommunication providers use a combination of network infrastructure, advanced technologies, and ongoing performance analysis to maintain and improve these QoS metrics.

The Union Logic team streamlined data ingestion pipelines & processed the QoS streaming data with feature engineering as step 1, followed by training model to find QoS outliers, apply business logic, and send corrective signals to the downstream systems .

Our Telecom Customer was able to automate the QoS service levels with significant productivity improvement in identifying Service Degradation and addressing it proactively.