Scalable Packet Loss Recovery With Adaptive Redundancy Control
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Solution Overview
Problem
Existing methods for packet loss recovery in lossy network systems are limited by their inability to adapt to varying network conditions and require significant changes to existing encoders and decoders, making them inflexible and inefficient.
Innovation Solution
A system that encodes source signals with a variable bit rate, controlled by a bit rate controller, to adapt to packet loss statistics and network conditions, allowing for real-time adjustment of redundancy to enhance packet loss robustness without requiring changes to legacy encoders or decoders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If sender-based methods with constant redundancy bit rate are used, then packet loss protection is improved, but adaptability to varying network conditions deteriorates
Solution Approach 1:
The patent implements dynamic adaptability by allowing the receiver to autonomously adjust the interpretation of received data based on varying network conditions and packet loss patterns, transforming a static constant bit rate system into a dynamically adaptive one without requiring encoder changes
Solution Approach 2:
The invention changes the parameter of redundancy interpretation at the receiver side, allowing the same transmitted data to be interpreted with varying degrees of redundancy extraction depending on current network conditions, thereby achieving adaptability without modifying the transmission parameters
2Reliability
If MDC-based strategies are used, then packet-loss robustness is improved, but system complexity and integration difficulty increase
Solution Approach 1:
The patent extracts the complexity of packet loss recovery from the encoder side and relocates it to the receiver side, where the receiver autonomously performs adaptive interpretation of received data, thereby simplifying the encoder while maintaining robustness
Solution Approach 2:
The receiver is empowered with self-service capabilities to autonomously adapt its decoding strategy based on observed network conditions and packet loss patterns, eliminating the need for complex coordinated control between encoder and decoder
3Reliability
If vector quantizers with predetermined lookup tables are used, then packet loss recovery is improved, but flexibility and computational efficiency deteriorate
Solution Approach 1:
The patent replaces static predetermined lookup tables with dynamic adaptive interpretation at the receiver, allowing the system to flexibly adapt to varying network conditions and packet loss patterns without being constrained by pre-computed tables
Solution Approach 2:
The invention performs preliminary encoding with constant bit rate at the sender, then applies adaptive recovery actions at the receiver based on actual network conditions, separating the preliminary encoding from the adaptive recovery process
4Measurement precision
If multiple statistical models are trained for different rates and scenarios, then packet loss estimation accuracy is improved, but computational burden and system complexity increase
Solution Approach 1:
The patent implements a universal single statistical model at the receiver that can adapt to multiple different rates and packet loss scenarios through autonomous parameter adjustment, eliminating the need for multiple specialized models trained for different conditions
Solution Approach 2:
The receiver employs feedback mechanisms to continuously monitor network conditions and packet loss patterns, using this information to dynamically adjust its interpretation strategy, thereby achieving scenario-specific accuracy with a single adaptive model
Data Source
AI summary
A system for transmitting data packets representing a source signal across a packet data network is provided. Additionally provided are methods and an apparatus for encoding parameters representing the source signal and also decoding these parameters. The system allows adaptation to the loss scenario of data packets transmitted across the packet data network. A redundancy encoding is generated with a bit rate continuously scalable, the bit rate being provided by a bit rate controller that uses input from the network and packet-loss rate information. The specification can be changed for each coding block. At the decoder, recovery is performed by a parameter estimator based on a dynamically generated statistical model of the effect of the quantizers. The method may be added to existing lossy source coding systems or may be used to enhance the quality of the reconstructed source signal even in scenarios without packet loss.