Symbol-Encoded FEC Transport for Low-Latency Error Correction
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Solution Overview
Problem
Existing data transmission methods face challenges in efficiently correcting errors in high-speed transmission streams, particularly when using low-cost FEC algorithms, as errors can result in multiple bit errors due to corrupted symbols, leading to increased complexity and latency.
Innovation Solution
Implementing a method to transport FEC codes in a symbol-encoded transmission stream by encoding data streams into symbols, generating and merging FEC codes with data symbols, and correcting errors before decoding, which allows for the use of simpler FEC algorithms like Hamming codes, reducing complexity and latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If FEC codes are generated before symbol encoding, then error correction capability is provided, but a single bit error in transmission can cause multiple bit errors in received data due to corrupted symbols
Solution Approach 1:
The patent applies preliminary action by generating FEC codes from the data stream before symbol encoding occurs. The FEC generator creates redundancy bits that are then encoded into symbols along with the data. This preliminary error correction setup allows the receiver to detect and correct errors that occur during transmission, preventing single bit errors from propagating into multiple bit errors through symbol decoding.
Solution Approach 2:
The patent implements beforehand cushioning by inserting FEC parity bits into the data stream before symbol encoding. These parity bits act as a protective cushion against transmission errors. When errors occur during transmission, the FEC decoder at the receiver can use these pre-positioned parity bits to cushion against the harmful effects of symbol corruption, correcting errors before they propagate through the decoding process.
2Reliability
If complex FEC algorithms like Reed-Solomon or LDPC are used to correct byte errors, then error correction capability improves, but encoder and decoder complexity increases
Solution Approach 1:
The patent applies parameter changes by modifying the FEC code parameters to match the symbol encoding structure. Instead of using fixed complex codes, the system configures the FEC generator to create parity bits that are integrated into the symbol stream at specific intervals. This parameter adjustment allows simpler Hamming codes to achieve byte-level error correction by aligning the FEC block size with the symbol structure, reducing complexity while maintaining reliability.
Solution Approach 2:
The patent uses copying by replicating the FEC encoding process across multiple data blocks in a systematic manner. Rather than implementing a single complex FEC scheme, the system applies simplified FEC codes repeatedly across segmented data streams. This copying approach distributes the error correction function across multiple simpler instances, achieving robust byte error correction without requiring high complexity in any single encoder or decoder unit.
3Productivity
If FEC codes are integrated into the symbol stream, then transmission efficiency improves, but error correction must handle the combined data and parity symbols
Solution Approach 1:
The patent applies merging by combining the data stream and FEC parity bits into a unified symbol stream for transmission. The FEC generator integrates parity bits with data bits, and the symbol encoder converts this combined stream into transmission symbols. At the receiver, the symbol decoder extracts both data and parity symbols, and the FEC decoder processes them together to correct errors. This merging eliminates the need for separate transmission channels, improving efficiency while the systematic extraction and processing maintain manageable complexity.
Solution Approach 2:
The patent uses segmentation by dividing the combined data and parity symbol stream into manageable blocks for FEC decoding. The receiver segments the incoming symbol stream to identify data symbols and parity symbols, processing them in organized groups. This segmentation allows the FEC decoder to handle the combined stream systematically, correcting errors in data blocks using their corresponding parity blocks without being overwhelmed by the integrated nature of the transmission stream.
Data Source
AI summary
A method to transport forward error correction (FEC) codes in a symbol encoded transmission stream includes encoding a data stream from a data source into data symbols using computing circuits, generating first FEC codes from the data symbols using the computing circuits, encoding the first FEC codes into first FEC symbols using the computing circuits, merging the data symbols and the first FEC symbols into the transmission stream using the computing circuits, and transmitting the merged transmission stream to a sink device using the computing circuits. The encoding of the data stream into the data symbols and the encoding of the first FEC codes into the first FEC symbols may include the same encoding technique.


