XR Data Coding by QoS Layer for Low-Latency Wireless Transmission
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Solution Overview
Problem
The transmission of extended reality (XR) data in wireless networks is prone to radio channel fading, leading to retransmissions that increase transmission delay and compromise real-time transmission requirements, resulting in poor user experience with issues like frame freezing and dizziness.
Innovation Solution
A coding method that distinguishes between different dimensions or quality of service (QoS) requirements of XR data, allowing for efficient coding based on specific XR data types, such as base layer and enhancement layer data, or in-field of view and out-of-field of view data, to improve coding efficiency and resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If retransmission is performed to ensure data transmission reliability in wireless networks, then transmission reliability is improved, but transmission delay increases and real-time transmission requirements cannot be ensured
Solution Approach 1:
The XR data stream is segmented into multiple codeblocks, with each codeblock independently coded and transmitted. This segmentation allows the system to transmit multiple independent data units simultaneously, reducing the need for retransmission of entire data streams and thereby reducing transmission delay while maintaining reliability.
Solution Approach 2:
Forward error correction codes are applied preliminarily to the XR data before transmission. By pre-encoding the data with error correction capabilities, the system can correct transmission errors without requiring retransmission, thus improving reliability while avoiding the time loss associated with retransmission protocols.
2Ease of manufacture
If traditional coding methods are used for XR data transmission, then implementation simplicity is maintained, but coding efficiency is insufficient and resource utilization is low
Solution Approach 1:
Different coding parameters and configurations are applied to different codeblocks based on their specific requirements. The system can selectively apply different error correction codes, code rates, or coding schemes to different portions of the XR data stream, optimizing coding efficiency for each segment while maintaining overall implementation feasibility.
Solution Approach 2:
The coding scheme is made dynamic and adaptive, allowing the system to adjust coding parameters in real-time based on channel conditions, data priority, and QoS requirements. This dynamic approach improves coding efficiency and resource utilization while maintaining a level of implementation simplicity through standardized adaptation mechanisms.
Data Source
AI summary
A coding method and an apparatus are provided. XR data of different dimensions or different QoS requirements are distinguished during coding.