Video Codec Importance Signaling for RAN-Aware Traffic 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 differing quantitative constraints and configurations, making it challenging to optimize transmission strategies for video traffic with increasing resolution demands.
Innovation Solution
A method to derive video codec data units' importance without decoding, using video codec syntax parsing and semantic extraction, and configure RAN functionality based on video codec awareness, leveraging hybrid video codecs' hierarchical structures to decorate data units with importance information for optimized transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If video decoding is performed to determine NAL unit importance, then measurement precision of semantic information is improved, but processing time and system 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, without performing complete decoding. This selective extraction approach obtains sufficient semantic information (principle of taking out) while avoiding the time-consuming full decoding process, thus resolving the contradiction between measurement precision and processing time.
Solution Approach 2:
The patent performs preliminary extraction of syntax elements and semantic information before actual importance calculation. By preparing and organizing the necessary information in advance (preliminary action), the system can quickly determine importance values without needing to perform time-consuming decoding operations at the moment of importance assessment.
2Loss of information
If complete video decoding is performed to extract semantic information, then information completeness is improved, but processing complexity and computational resources increase
Solution Approach 1:
The patent extracts only the specific syntax elements and semantic information required for importance determination, rather than performing complete video decoding. This selective extraction obtains sufficient semantic information while significantly reducing processing complexity and computational resource requirements.
Solution Approach 2:
The patent applies partial action by extracting and processing only the necessary portion of video data (syntax elements and semantic information) needed for importance determination, rather than performing excessive complete decoding. This partial processing approach maintains information completeness for the specific task while reducing overall processing complexity.
3Productivity
If traditional network scheduling is used without codec awareness, then system simplicity is maintained, but transmission optimization for video traffic is insufficient
Solution Approach 1:
The patent performs preliminary configuration of RAN functionality with codec awareness parameters and importance indication mechanisms before video transmission. This preliminary setup (preliminary action) enables the network to recognize and optimize video traffic based on NAL unit importance, improving transmission efficiency while managing complexity through structured pre-configuration.
Solution Approach 2:
The patent introduces an intermediary mechanism (importance indication and RAN awareness configuration) between the video source and network scheduler. This intermediary layer translates codec-specific semantic information into network-understandable priority indicators, enabling optimized scheduling without requiring the network to perform complex codec-specific processing, thus balancing transmission optimization with manageable complexity.
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.