eMBMS Video Quality Analysis via Packet Loss Metrics
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Solution Overview
Problem
Current solutions for evaluating video quality in eMBMS networks lack insight into the specific factors affecting end-user perception, providing only a single Mean Opinion Score (MOS) that does not identify the source of quality issues.
Innovation Solution
A system and method that include monitoring probes and a processor to capture and analyze video data, determining the number of lost data packets, calculating the probability of unrecoverable losses, and calculating a video quality index, while also measuring packet loss concealment and forward error correction effectiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a single Mean Opinion Score (MOS) is provided for video quality evaluation, then the evaluation process is simplified, but insight into specific factors affecting end-user perception is lost
Solution Approach 1:
The patent segments the overall video quality evaluation into multiple distinct components: packet loss metrics, blur metrics, audio quality metrics, and synchronization metrics. Each component is measured and reported separately, providing detailed insight into specific quality issues while maintaining an organized evaluation structure.
Solution Approach 2:
The patent transitions from a single-dimension MOS score to a multi-dimensional quality assessment framework. Multiple quality parameters are measured simultaneously across different dimensions (video, audio, synchronization, packet loss), creating a comprehensive quality profile that preserves detailed information while remaining manageable.
2Measurement precision
If detailed quality metrics are measured and reported, then insight into quality issues is enhanced, but the complexity of the evaluation system increases
Solution Approach 1:
The evaluation system is segmented into specialized measurement modules, each responsible for specific quality aspects (video packet loss, audio packet loss, blur detection, synchronization). This modular segmentation reduces overall system complexity by dividing complex measurement tasks into manageable, independent components.
Solution Approach 2:
The patent introduces intermediary processing elements that capture and analyze specific quality metrics from the video stream. These intermediaries (monitoring probes, analysis modules) act as mediators between the video transmission system and the evaluation framework, enabling detailed measurement without overwhelming system complexity.
3Loss of information
If packet loss and error correction effectiveness are analyzed, then video quality understanding is improved, but the processing requirements increase
Solution Approach 1:
The patent applies partial analysis by focusing measurement efforts on critical quality parameters most likely to impact user perception (packet loss, blur, audio quality, synchronization). Rather than analyzing every possible parameter, the system selectively measures the most impactful factors, reducing processing requirements while maintaining evaluation effectiveness.
Solution Approach 2:
The patent replaces complex full-video-rendering and subjective-quality-assessment mechanisms with streamlined metric-based measurements. Instead of requiring extensive processing to simulate human perception, the system uses direct measurements of key quality parameters (packet loss rates, synchronization offsets, blur detection) that correlate with user experience but require less computational resources.
Data Source
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AI summary
A system for evaluating quality of video delivered over a telecommunications network is provided. The system includes one or more monitoring probes coupled to one or more network interfaces providing direct communication between two or more networked devices. The monitoring probes are adapted to capture video data from the network interfaces. The system further includes a processor adapted to analyze the data captured by the monitoring probes. The processor is operatively configured to determine a number of lost data packets within the captured video data. The processor is further operatively configured to determine probability of unrecoverable losses within the captured video based on the determined number of lost data packets. The processor is also operatively configured to calculate a video quality index value based on the determined probability of unrecoverable loses.