Article 4 — Measuring QoE with Synthetic Test Calls: Validating Experience in Real Time

Inferring QoE from handset telemetry is powerful — but sometimes you need proof. A direct measurement. A controlled test. A way to validate what the data suggests.

That’s where synthetic test calls come in.

QoE AI Insights can initiate lightweight, controlled videoconferencing sessions against dedicated test infrastructure to measure real-time performance under current network conditions. These aren’t simulations — they’re real protocol-level interactions designed to mimic actual user behaviour, without touching production collaboration environments.

This article explores how test calls work, what they measure, and how they complement passive telemetry to provide a complete picture of videoconferencing readiness.

What Is a Synthetic Test Call?

A synthetic test call is a short, automated video/audio session initiated by the device or monitoring agent. It uses the same protocols and media patterns as real conferencing apps (e.g. WebRTC-style flows, representative codecs), but connects to QoE AI Insights test infrastructure, not live collaboration platforms.

These calls:

• Connect to controlled, non-production test endpoints

• Use lightweight video and audio payloads

• Run for a short duration (e.g. 30–60 seconds)

• Measure real-time performance metrics

• Avoid impacting user-facing services or licenses

They’re designed to answer one question:

“If a real call happened now, how would it perform?”

What Test Calls Actually Measure

During a synthetic test call, QoE AI Insights captures:

• Jitter — variation in packet arrival times

• Packet loss — missing or corrupted packets

• Latency — round-trip time

• Throughput — sustained data rate

• Stability — connection consistency

• Codec-like adaptation — changes in effective bitrate and resolution under stress

• Recovery behaviour — how the stream responds to degradation

These metrics are analysed in real time and mapped to expected user experience outcomes.

Why Test Calls Matter

Ambient telemetry tells you what the device is experiencing.

Test calls tell you how the network behaves under realistic media load.

Together, they provide:

• Validation — confirming inferred QoE predictions

• Benchmarking — comparing performance across regions, devices, or networks

• Diagnostics — pinpointing root causes of poor experience

• Readiness checks — verifying meeting quality before users connect

This enables proactive assurance — not just reactive troubleshooting.

How Test Calls Fit Into the QoE AI Insights Framework

QoE AI Insights combines:

• Passive telemetry — continuous, ambient data from the handset

• Synthetic test calls — active measurement against dedicated test infra

• Network integration — correlation with RAN, transport, and core metrics

• Centralized intelligence — crowd-sourced insights across millions of devices

This creates a multi-layered, validated view of experience — grounded in both inference and measurement.

From Measurement to Action

Test call results can trigger:

• Alerts for degraded regions or access types

• Automated support workflows

• Dynamic traffic shaping or prioritization

• SLA enforcement and reporting

• Experience-aware orchestration

They’re not just diagnostic — they’re operational.

Looking Ahead: Article 5 — Centralized QoE Intelligence at Scale

Next, we’ll look at how QoE AI Insights aggregates telemetry and test-call data across millions of devices to build a real-time, geo-aware map of experience — and how that powers network-wide intelligence and, ultimately, automation.