Tree-Structured FEC Coding for Sequential Error Correction
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Solution Overview
Problem
Communication networks, particularly those involving optical signals, face signal degradation due to polarization mode dispersion, polarization dependent loss, state of polarization rotation, amplified spontaneous emission, and chromatic dispersion, leading to increased bit error ratios and reduced signal quality.
Innovation Solution
A transmitter device generates an encoded vector by encoding payload information with parity information using forward error correction (FEC) codes, such as Bose, Chaudhuri, and Hocquenghem codes, and transmitting it over a communication channel. The receiver device decodes the signal using recursive mathematical operations to recover the original payload information, employing FEC codes like Reed-Solomon and repetition codes to correct errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If forward error correction encoding is applied to correct signal degradation, then bit error ratio is reduced and signal quality is improved, but device complexity and computational overhead increase
Solution Approach 1:
The encoding process is divided into multiple stages: generating intermediate codewords through recursive mathematical operations, then combining these codewords to form the final encoded vector. This segmentation allows complex encoding to be broken down into manageable steps that can be implemented efficiently in hardware or software.
Solution Approach 2:
The patent employs nested recursive operations where codewords are generated through repeated application of mathematical operations, and these codewords are then nested within the final encoded vector structure. This nested approach enables systematic error correction while maintaining computational efficiency.
2Reliability
If multiple FEC codewords are calculated using recursive mathematical operations, then error correction capability is enhanced, but processing time and computational resources increase
Solution Approach 1:
The encoding process uses periodic recursive mathematical operations to generate multiple codewords in a systematic sequence. This periodic structure allows for efficient processing by repeating the same mathematical operations across different data blocks, enabling pipeline implementation and reducing overall processing time.
Solution Approach 2:
The patent changes mathematical parameters during the encoding process, using different recursive operations and combining codewords with varying weights. This parameter variation allows the system to adapt error correction strength to channel conditions while maintaining efficient processing through standardized mathematical building blocks.
Data Source
AI summary
A transmitter (200) generates (602) an encoded vector (404) by encoding (406) a data vector (402), the encoded vector representing payload information and parity information. The encoding is mathematically equivalent to calculating three or more forward error correction (FEC) codewords from the data vector and then calculating the encoded vector from the codewords, at least one codeword being calculated from at least one recursion of a mathematical operation, and at least one codeword comprising more than 6 terms. The transmitter transmits (604) a signal representing the encoded vector over a communication channel. A receiver (300) determines (702) a vector estimate (502) from the signal and recovers (716) the data vector from the vector estimate by sequentially decoding (706, 710, 714) the codewords, wherein at least one codeword that is decoded earlier in the decoding enhances an estimate of at least one codeword that is decoded later in the decoding.