De-Correlated Encoding for Bandwidth-Adaptive Data Recovery
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Solution Overview
Problem
Existing data transmission processes face challenges in bandwidth adaptation, where the bandwidth required for encoded data often exceeds the pre-configured or available bandwidth at the decoding apparatus, leading to incomplete data reception.
Innovation Solution
The proposed method involves an encoding apparatus that encodes data using an encoding model, performs de-correlation on the encoded data to obtain de-correlated encoded data, and sends these data. The de-correlation process ensures that the data pieces are independent and uncorrelated, allowing for bandwidth adaptation even with limited bandwidth resources at the decoding apparatus.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If all N pieces of encoded data are transmitted to ensure complete information recovery, then the completeness of data reception is improved, but the bandwidth resource requirement increases
Solution Approach 1:
The encoded data is divided into N pieces through an output layer with N nodes, where each node outputs one piece of encoded data. This segmentation allows the data to be distributed across multiple pieces, enabling selective reception based on bandwidth availability while maintaining the ability to reconstruct the original data from any sufficient subset of pieces.
Solution Approach 2:
The system changes the parameter of data independence through de-correlation processing. By making the N pieces of encoded data independent and uncorrelated, the system enables flexibility in bandwidth adaptation - the decoding apparatus can successfully reconstruct data from M pieces where M is less than N, thus reducing the required bandwidth resource while maintaining reliability.
2Adaptability or versatility
If de-correlation processing is applied to make encoded data pieces independent, then the bandwidth adaptation capability is improved, but the encoding complexity increases
Solution Approach 1:
The de-correlation processing is performed in advance during the encoding phase, before transmission. This preliminary action ensures that the encoded data pieces are already independent and uncorrelated, enabling the decoding apparatus to adapt to various bandwidth conditions without requiring complex real-time processing. The complexity is shifted to the encoding end where it can be handled more efficiently.
3Quantity of substance
If M pieces of de-correlated encoded data are transmitted with M < N, then the bandwidth resource consumption is reduced, but the data reconstruction quality may deteriorate
Solution Approach 1:
The system is designed to transmit M pieces of encoded data where M is less than N, utilizing only the necessary portion of the encoded data for successful reconstruction. This partial action approach reduces bandwidth consumption while the de-correlation processing ensures that the M pieces transmitted contain sufficient independent information for accurate data reconstruction, preventing quality deterioration.
Data Source
AI summary
Example encoding/decoding methods, communication apparatus, and systems are provided. One example encoding method includes encoding first data by using an encoding model, to obtain N pieces of encoded data, where N is an integer greater than 2. De-correlation is performed on the N pieces of encoded data to obtain N pieces of de-correlated encoded data, where a part or all of the N pieces of de-correlated encoded data may be for determining second data, the second data is for restoring third data, and the third data is the first data, or an approximation degree between the third data and the first data is greater than a specified threshold The N pieces of de-correlated encoded data are sent.