Tornado FEC Parameter Selection for Reliable File Broadcasts
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Solution Overview
Problem
Communication systems face challenges in selecting optimal Tornado error correction parameters for efficient data delivery due to varying noise and interference levels, which affect the reliability and throughput of data transmission.
Innovation Solution
The system employs a method to select Tornado error correction parameters and graphs based on specific client identifiers, file size, outage duration, and broadcast data rate, using a processor to configure the Tornado EC encoder and decoder, ensuring effective error correction and recovery of lost data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If additional redundancy symbols are included in error correction codeword, then error correction capability is improved, but instantaneous throughput deteriorates
Solution Approach 1:
The system dynamically adjusts the number of redundancy symbols and block sizes based on real-time channel conditions, noise levels, and interference characteristics. The processor selects optimal Tornado code parameters adaptively, allowing the error correction capability and throughput to be optimized for current transmission conditions rather than using fixed parameters.
Solution Approach 2:
The invention changes key parameters of the Tornado error correction code including block size, number of redundancy symbols, and graph structure based on measured channel conditions. By varying these parameters dynamically, the system achieves better error correction performance when needed while maintaining higher throughput when channel conditions are good.
2Reliability
If larger block sizes are used in FEC coding, then error correction efficiency is improved, but latency increases
Solution Approach 1:
The system dynamically adjusts block size based on channel conditions and service requirements. For time-sensitive applications or good channel conditions, smaller block sizes are selected to reduce latency. For poor channel conditions or non-time-critical data, larger block sizes are used to maximize error correction efficiency.
Solution Approach 2:
The data stream is segmented into multiple blocks of varying sizes rather than using a single fixed block size. This allows different segments to be processed with appropriate block sizes tailored to their specific requirements, balancing error correction efficiency with latency constraints for different portions of the data.
3Reliability
If higher redundancy is applied, then data reliability is improved, but file size inflation increases
Solution Approach 1:
The system adjusts the redundancy ratio parameter of the Tornado code based on channel conditions and data importance. For critical data or poor channel conditions, higher redundancy is applied. For less critical data or good channel conditions, lower redundancy is used to minimize file size inflation.
Solution Approach 2:
Different redundancy levels are applied to different portions of the data based on their importance and the channel conditions for their transmission. Critical data segments receive higher redundancy protection while less critical segments use lower redundancy, optimizing the overall balance between reliability and file size.
Data Source
AI summary
Methods and apparatus to select Tornado forward error correction parameters for delivery systems are disclosed. A disclosed example system includes a transmitter station comprising a processor to select a Tornado error correction parameter based on an error correction configuration for a file and to indicate to a receiver the selected Tornado error correction parameter, and a Tornado error correction circuit to encode the file based on the selected Tornado error correction parameter.