Adaptive Video Encoder for Low-Latency Streaming
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Solution Overview
Problem
Current wireless solutions for transmitting multimedia streams, including audio, video, and control information, often suffer from high latency, error resiliency issues, and quality degradation, particularly in wireless networks like WiFi, which fail to match the performance of direct-wired connections.
Innovation Solution
A method and system for transmitting multimedia streams over a network that dynamically adjusts video encoding parameters based on real-time channel conditions, using techniques such as sub-frame rate adaptation and maintaining a headroom between the channel bit rate and encoded video bit rate to ensure low latency and high-quality transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If wireless transmission is used to enable mobility and connect various sources with displays, then ease of operation and adaptability are improved, but latency increases and reliability deteriorates compared to wired connections
Solution Approach 1:
The system dynamically adjusts video encoding parameters including bit rate, resolution, and frame rate based on real-time network conditions to optimize transmission performance. The encoder continuously monitors channel state and adapts encoding settings to maintain low latency while ensuring reliable wireless transmission
Solution Approach 2:
The patent changes multiple encoding parameters simultaneously (bit rate, resolution, frame rate) to adapt to varying network conditions. By adjusting these parameters dynamically, the system achieves low-latency transmission over wireless networks while maintaining video quality and reliability
2Reliability
If adaptive encoding is used to optimize transmission for varying network conditions, then reliability and quality are improved, but device complexity increases
Solution Approach 1:
The video stream is divided into independent slices at the macroblock level, allowing selective transmission and error concealment. When network conditions deteriorate, only critical slices are transmitted or retransmitted, improving error resiliency without requiring complete re-encoding of entire frames
Solution Approach 2:
The encoding system dynamically adjusts complexity based on network conditions. During good network conditions, higher complexity encoding provides better quality. During poor conditions, the system reduces encoding complexity while maintaining reliability through adaptive parameter selection and error resiliency mechanisms
3Manufacturing precision
If higher video bit rate is used to maintain quality, then manufacturing precision of video quality is improved, but loss of energy and bandwidth increases
Solution Approach 1:
The system dynamically changes video encoding parameters including bit rate, resolution, and frame rate based on network conditions and quality requirements. By intelligently adjusting these parameters, the system maintains acceptable video quality while minimizing bandwidth consumption and energy usage
Solution Approach 2:
The patent applies partial action by transmitting only essential video information at reduced bit rates when network conditions are poor. The adaptive encoder selectively maintains quality for critical frames while reducing quality for less important frames, optimizing the trade-off between video quality and bandwidth consumption
Data Source
AI summary
Systems and methods for transmitting a multimedia stream over a communication link on a network are disclosed. The systems and methods adaptively adjust encoding parameters based on monitoring changing conditions of the network. A transmitter includes an adaptive-rate encoder that adaptively adjusts a video encoding bit rate in response to changing conditions of the communication link. The encoder maintains tight rate control by utilizing slice processing and sub-frame rate adaptation, as well as maintaining a headroom between the channel bit rate and the video encoding bit rate. The adaptive-rate encoder also embeds intra-frame constraints in predictive frames traffic in order to reduce latency.