Video Codec Importance Indication for Decode-Free RAN Scheduling
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Solution Overview
Problem
Current communications networks struggle to deliver high-fidelity quality of experience (QoE) for emerging applications like AR/VR/XR and cloud gaming due to the lack of video codec awareness, leading to challenges in optimizing transmission strategies for high-resolution video traffic with varying quantitative constraints.
Innovation Solution
Implementing a method to derive video codec data units' importance without decoding, based on video codec syntax parsing and semantic extraction, and configuring RAN functionality with reduced latency, using a graphical directed information flow model to annotate video data units for optimized scheduling and transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If video decoding is performed to determine NAL unit importance, then measurement precision of video content importance is improved, but processing time and computational complexity increase significantly
Solution Approach 1:
The patent extracts only the essential syntax elements and semantic information needed for importance determination from the video bitstream, rather than performing complete video decoding. This selective extraction approach obtains sufficient information about NAL unit importance (such as frame type, picture order count, and other coding parameters) without the computational overhead of full decoding, thereby resolving the contradiction between measurement precision and processing time
Solution Approach 2:
The patent performs syntax parsing and semantic information extraction in advance, before actual video decoding occurs. By pre-processing the bitstream to identify and extract relevant importance indicators, the system prepares the necessary information ahead of time, enabling fast importance determination when needed without requiring time-consuming decoding operations
2Measurement precision
If complete video decoding is performed to extract semantic information, then information extraction accuracy is improved, but device complexity and computational resources increase
Solution Approach 1:
The patent extracts only the specific semantic information elements required for importance determination (such as NAL unit type, frame type, picture order count, and other relevant syntax elements) from the video bitstream, rather than performing complete video decoding to obtain all possible information. This selective extraction reduces computational complexity while maintaining the accuracy needed for importance assessment
Solution Approach 2:
The patent segments the video processing task into distinct stages: syntax element detection, semantic information extraction, and importance determination. By dividing the processing into separate modular stages, the system can extract only the necessary semantic information at each stage without requiring complete decoding, thereby reducing overall device complexity while maintaining extraction accuracy
3Productivity
If video codec awareness is implemented at RAN level, then transmission optimization is improved, but RAN complexity increases
Solution Approach 1:
The patent introduces an intermediary module at the RAN level that acts as a bridge between the video source and the transmission network. This intermediary performs syntax parsing and semantic information extraction to generate importance indicators, which then guide transmission scheduling and resource allocation. By placing this intelligent intermediary at the RAN boundary rather than throughout the entire network, transmission optimization is achieved while limiting the increase in RAN complexity to a manageable scope
Data Source
AI summary
Apparatuses, methods, and systems are disclosed for video codec importance indication and RAN awareness configuration. An apparatus includes a processor that detects a plurality of video coded network abstraction layer (“NAL”) units of a video coded stream, extracts semantic information associated with the plurality of the NAL units, combines the extracted semantic information associated with the plurality of NAL units to form a plurality of feature sets that is correspondingly synchronized with the plurality of NAL units that enclose the extracted semantic information, determines an information-to-importance value for each of the plurality of NAL units based on the plurality of feature sets without performing video decoding of the video coded stream, and indicates the determined information-to-importance value for each of the plurality of NAL units of the determined video codec specification to a video coded traffic-aware transceiver for scheduling video traffic based on the indicated information-to-importance value.