XR-Aware RAN Frame Error Concealment for Temporal Error Control
Solution Overview
Problem
Existing mobile communication technologies face challenges in optimizing latency-sensitive throughput-sensitive applications like XR, particularly in managing temporal error propagation, frame error concealment, and quality of service for applications such as virtual reality, augmented reality, and mixed reality.
Innovation Solution
Implementing cross-layer optimization techniques in XR-aware RAN to limit temporal error propagation through frame error concealment, I-frame-on-demand, multi-layer-encoding multiplexing, and late-frame handling, including network communication with UE for error reporting and resource configuration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If frame error concealment is implemented to limit temporal error propagation, then quality of experience is improved, but frame error rate requirements become more relaxed
Solution Approach 1:
The patent converts the harmful effect of frame errors into a beneficial mechanism by implementing frame error concealment. When frame errors occur, the system actively conceals them using previously decoded frames and motion compensation, transforming the error propagation problem into a feature that maintains continuous video decoding and improves overall quality of experience.
Solution Approach 2:
The patent applies beforehand cushioning by decoding frames in advance and storing them for potential error concealment. The system prepares reference frames before errors occur, enabling rapid recovery when frame errors are detected. This proactive approach cushions against the impact of temporal error propagation and maintains service continuity.
2Loss of time
If I-frame on-demand is optimized to reduce turnaround time, then latency is improved, but network resources are consumed
Solution Approach 1:
The patent implements preliminary action by pre-configuring network parameters and pre-decoding frames before they are actually needed. The system anticipates I-frame requests and prepares the necessary resources in advance, reducing the turnaround time when errors occur while avoiding unnecessary resource consumption through demand-driven activation.
Solution Approach 2:
The patent applies dynamics by making the I-frame transmission mechanism adaptive and demand-driven. The system dynamically adjusts its behavior based on actual error conditions and user needs, activating resource-intensive I-frame retransmission only when necessary rather than continuously, thus optimizing the balance between latency reduction and resource consumption.
3Productivity
If multi-layer encoding multiplexing is implemented to optimize QoS, then throughput is improved, but device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the video stream into multiple independent layers (base layer and enhancement layers) with different quality and latency characteristics. Each layer can be encoded and transmitted separately, allowing the system to optimize throughput by selectively transmitting and decoding layers based on network conditions and QoS requirements without requiring complete decoding of all layers.
Data Source
AI summary
A network communicates an extended reality (XR) traffic with a user equipment (UE) with frame error concealment to limit a duration of temporal error propagation. The network also transmits a report of failure or a request for retransmission to the UE in an event of a network transmission failure.