Free-Space Optical Transport Data Encoding for Deep-Fading Reliability
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Solution Overview
Problem
Existing communication systems face challenges in improving transmission and reception efficiency, particularly in free space optical communications, due to interference, interception, and jamming, and require enhanced encoding and error correction techniques to maintain security and reliability.
Innovation Solution
Implementing an nb/mb encoding scheme, such as 8b/10b, with reliability metrics based on log likelihood ratios (LLRs) to assign different reliability levels to bits in payload data words, and using LDPC forward error correction with on/off keying modulation for free space optical communications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If free space optical communication is used to improve security and minimize signal spread, then interception and jamming probability is reduced, but transmission reliability deteriorates in deep fading environments
Solution Approach 1:
The patent applies preliminary action by performing forward error correction encoding before transmission to preemptively protect against channel errors. The LDPC encoder processes the encoded symbols in advance, generating redundant information that will be used to correct errors during reception without requiring retransmission.
Solution Approach 2:
The patent implements beforehand cushioning by adding redundancy through nb/mb encoding and LDPC encoding. This creates a buffer against errors by embedding additional information that can compensate for signal degradation and corruption during transmission through deep fading environments.
2Reliability
If nb/mb encoding scheme with reliability metrics is implemented to improve error correction, then transmission reliability is improved, but device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the error correction process into distinct stages: first nb/mb encoding to map n-bit words to m-bit symbols, then LDPC encoding on the encoded symbols, and finally separate decoding stages. This segmentation allows each component to be optimized independently and processed in manageable steps.
Solution Approach 2:
The patent implements local quality by assigning different reliability metrics to different bits based on their individual characteristics. The system evaluates the reliability of each received bit separately using log-likelihood ratios, allowing the decoder to focus computational resources on correcting the most uncertain bits while accepting well-received bits with minimal processing.
3Reliability
If forward error correction is applied to improve communication reliability, then error correction capability is improved, but transmission efficiency decreases
Solution Approach 1:
The patent applies parameter changes by using nb/mb encoding to map n-bit words to m-bit symbols, changing the representation of data to enable more efficient error correction. This parameter transformation allows the system to achieve better error correction performance while managing the overhead through optimized symbol mapping and LDPC code rate selection.
Data Source
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AI summary
Processing signals is disclosed. A method includes receiving a signal transmission with a nb/mb encoding scheme that maps n-bit words to m-bit symbols. In this scheme, m > n. The method further includes, for a first payload data word in the transmission, determining that the first payload data word corresponds to a valid payload data word, and as a result, assigning a first reliability metric to bits in the first payload data word. The method further includes for a second payload data word in the transmission, determining that the second payload data word does not correspond to a valid payload data word, and as a result, assigning a second reliability metric to bits in the second payload data word. The method further includes performing signal decoding using the assigned reliability metrics.