Video Stream Loss Estimation Using RTP Headers
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Solution Overview
Problem
Current methods for estimating the mean opinion score (MOS) of video services in mobile networks are complex and impractical due to the need for software installation on each mobile device, and they fail to account for frame loss degradation and the degree of frame loss, especially in encrypted video streams.
Innovation Solution
A method that identifies and estimates loss in video streams using only header information and frame size, determining reference average sizes and occurrence frequencies during a learning period, allowing for loss calculation in subsequent periods without requiring dedicated software on receiving entities, and accounting for the impact of I and P frame losses on subsequent packets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex MOS estimation models with multiple parameters are used, then measurement precision is improved, but device complexity and ease of operation deteriorate due to software installation requirements on each mobile device
Solution Approach 1:
The patent extracts the MOS estimation function from the mobile device and relocates it to the network side. By using network probes to capture packet information and calculate MOS remotely, the system eliminates the need for complex software installation on each device while maintaining estimation accuracy through network-based processing of packet loss, delay, and jitter data
Solution Approach 2:
The patent introduces a network probe as an intermediary entity that mediates between the video stream transmission and MOS calculation. This intermediary captures packet information, performs loss analysis, and computes MOS metrics without requiring direct software presence on mobile devices, thus simplifying deployment while maintaining measurement precision
2Measurement precision
If traditional MOS estimation methods are used, then measurement precision is improved, but ease of operation deteriorates due to inability to handle encrypted video streams
Solution Approach 1:
The patent extracts the capability to analyze video quality metrics from the encrypted payload and focuses analysis on packet-level characteristics such as packet loss, delay, and jitter. These parameters can be measured from header information and transmission timing without decrypting the video content, enabling MOS estimation for encrypted streams through network performance analysis rather than content inspection
3Device complexity
If frame loss propagation is not considered, then calculation complexity is reduced, but measurement precision deteriorates due to incomplete loss accounting
Solution Approach 1:
The patent performs preliminary analysis during a learning period to establish baseline packet loss rates and frame type distributions. This preliminary data is stored and then used during normal operation to quickly estimate losses without complex real-time calculations. The system pre-characterizes the video stream's loss patterns, enabling accurate loss estimation through comparison with learned reference profiles rather than complex live analysis
Data Source
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AI summary
A method for estimating a loss of information in a video stream comprising video frames of different frame types, wherein the video stream is transmitted in a sequence of data packets, the method comprising during a first learning period of the video stream: - identifying the different frame types in the video stream, - determining a reference average size of at least some of the frame types in the video stream, determining a reference occurrence frequency how often at least some of the frame types occur in the video stream, wherein the reference average size and the reference occurrence frequency are determined using information provided in a header of the transmitted data packets, during a second time period of the stream: - identifying the different frame types in the video stream taking into account the reference average frame size, the reference occurrence frequency determined in the first learning period, and information provided in the header of the data packets in the second time period, - determining the size of at least some of the frames in the second time period, determining the loss of information in the video stream taking into account the reference average size, the reference occurrence frequency determined in the first learning period and the determined size of at least some of the frames in the second time period.