Dynamic Chapter Coding for Jamming-Resilient Data Transmission
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Solution Overview
Problem
Existing data transfer protocols, such as those using Reed-Solomon coding, face challenges in maintaining effective data transfer rates under jamming conditions, which lead to increased data corruption and datagram loss, making it difficult to recover data and requiring excessive buffering overhead.
Innovation Solution
A network transmission system that dynamically adjusts chapter size and redundancy of datagrams based on detected jamming conditions, using separate data and feedback channels to optimize data transfer by minimizing resends and ensuring complete cohort recovery, even under high loss rates, through self-tuning based on network latency and loss rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If Reed-Solomon coding is used to generate chapters of encoded datagrams for fault tolerance, then data recovery capability is improved, but buffering overhead increases
Solution Approach 1:
The patent dynamically adjusts chapter size and redundancy level based on real-time network conditions. When network loss rate increases, the system increases redundancy by adding more encoded datagrams to chapters. When network conditions improve, it reduces redundancy and chapter size. This dynamic adaptation resolves the contradiction by optimizing the balance between data recovery capability and buffering overhead according to actual network state.
Solution Approach 2:
The system changes key parameters including chapter size, redundancy level, and encoded datagram count based on measured network loss rates. By continuously monitoring network conditions and adjusting these parameters, the system maintains adequate data recovery capability while minimizing unnecessary buffering overhead in stable network conditions.
2Productivity
If chapter size is increased to reduce number of chapters transmitted, then transmission overhead is reduced, but impact of jamming increases
Solution Approach 1:
The patent implements dynamic chapter size adjustment based on network conditions. In normal conditions, larger chapters are used to reduce transmission overhead. When jamming is detected through increased loss rates, the system automatically reduces chapter size to limit the impact of any single chapter being lost to jamming. This dynamic approach resolves the contradiction between transmission efficiency and jamming vulnerability.
Solution Approach 2:
The system segments data into chapters of adaptive size. When jamming conditions are detected, it further segments data into smaller chapters, effectively applying segmentation dynamically. This allows the system to maintain smaller, less vulnerable chapters during jamming while using larger chapters during normal operation, resolving the contradiction between transmission efficiency and jamming impact.
3Reliability
If redundancy is increased to compensate for jamming losses, then data recovery is improved, but datagram transmission volume increases
Solution Approach 1:
The system dynamically adjusts the redundancy level (ratio of encoded to original datagrams) based on measured network loss rates. When jamming is detected and loss rates increase, the system increases redundancy to ensure data recovery. When network conditions improve, it reduces redundancy to minimize transmission volume. This dynamic adjustment resolves the contradiction between data recovery reliability and transmission volume.
4Device complexity
If fixed chapter size is used to simplify processing, then system complexity is reduced, but adaptability to varying network conditions deteriorates
Solution Approach 1:
The patent implements dynamic chapter size and redundancy adjustment based on real-time network condition monitoring. The system measures network loss rates and automatically adjusts chapter parameters to optimize performance for current conditions. This dynamic approach maintains adaptability to varying network conditions while using standardized Reed-Solomon coding algorithms to keep processing complexity manageable.
Solution Approach 2:
The system performs self-adjustment of chapter size and redundancy based on its own measurements of network conditions. It monitors loss rates, automatically modifies transmission parameters, and optimizes its own performance without external control. This self-service capability provides adaptability to network conditions while maintaining relatively simple processing through automated decision-making.
Data Source
AI summary
A method and system are provided for data transfer in a network where jamming conditions may occur. A sender at a first endpoint of the network includes a processor that implements fault-tolerant coding of cohorts of original datagrams that are converted into corresponding chapters of transformed datagrams such that the original datagrams are recovered by a receiver at a second endpoint of the network from a subset of the transformed datagrams of each chapter transferred over the network. In the presence of jamming, chapter size and redundancy of the coding are adjusted according to the level of jamming to enable datagram recovery with a minimum of resending over the network. The sending rate may also be tuned in reaction to changing network conditions based on messages from the receiver on a separate feedback channel to keep datagram loss rates below a specified upper bound.