LDPC Constellation Mapping for Unequal Bit Reliability
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Solution Overview
Problem
Low-density parity-check (LDPC) coding does not provide optimal performance when used with higher order modulation schemes such as 16-QAM, 64-QAM, and 256-QAM in digital television signal transmission systems, particularly due to the inherent inequity in bit reliability within the modulation constellation.
Innovation Solution
The implementation of parallel LDPC coding and symbol mapping processes tailored to LDPC coding, where bits from different substreams are mapped to specific regions of the symbol constellation map to address the reliability inequity, combined with block de-interleaving and non-binary LDPC coding, enhances coding performance and efficiency for higher order modulation formats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If LDPC coding is used with higher order modulation schemes (16-QAM, 64-QAM, 256-QAM), then data transmission rate and bandwidth efficiency are improved, but coding performance deteriorates due to bit reliability inequity within the modulation constellation
Solution Approach 1:
The bit stream is divided into multiple substreams, and bits from different substreams are mapped to different regions of the symbol constellation map. This segmentation allows different error protection levels to be applied to different bit positions, resolving the reliability issue while maintaining high transmission rates
Solution Approach 2:
Different regions of the symbol constellation map are assigned different error protection characteristics. Bits mapped to more reliable constellation regions receive different coding treatment than bits mapped to less reliable regions, optimizing overall system performance for higher order modulation schemes
2Reliability
If parallel LDPC coding and symbol mapping processes are implemented to address bit reliability inequity, then coding performance is improved, but device complexity increases
Solution Approach 1:
The bit stream is divided into multiple substreams that can be processed in parallel through separate LDPC coding paths. This segmentation enables improved error correction performance while distributing the processing load across multiple simpler parallel operations rather than one complex sequential operation
Data Source
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AI summary
Modern coding and modulation techniques have greatly improved the transmission and reception of signals. A method is described including receiving a signal de-mapping the signal into a first and second substream, decoding the first and second substream using a low density parity check decoding process, and combining the first and second decoded substream into a single data stream. An apparatus (700) is described including a symbol de-mapper (710) that receives a signal de-maps the modulation symbols in the signal into a first and second substream, a first decoder (730) that decodes the first substream using a low density parity check coding process at a first decoding rate, a second decoder (732) that decodes the second substream at a second encoding rate, and a combiner (740) that combines the first substream and the second substream into a single data stream.