Slepian-Wolf Code Partitioning for Flexible Multi-Source Rate Allocation
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Solution Overview
Problem
Existing Slepian-Wolf coding methods face challenges in practical implementation and rate allocation among encoders for distributed source coding, particularly in achieving arbitrary rate allocation while maintaining low encoding and decoding complexity.
Innovation Solution
The system employs channel code partitioning by generating sub-matrices from a generator matrix to create parity matrices for each correlated data source, allowing for flexible rate allocation and joint decoding with low complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If asymmetric codes are used to compress one source while using the other as side information, then lossless compression can be achieved at corner points of the Slepian-Wolf bound, but the system cannot flexibly allocate rates among encoders without time sharing which requires synchronization
Solution Approach 1:
The invention partitions a single channel code into multiple subcodes, where each subcode is assigned to a different encoder. This segmentation allows each encoder to operate independently with its own subcode, eliminating the need for time sharing and synchronization while enabling flexible rate allocation. The generator matrix is divided into sub-matrices, and parity matrices are generated for each subcode based on the corresponding sub-matrix.
2Adaptability or versatility
If multiple different codes are used to achieve arbitrary rate allocation among encoders, then rate flexibility is improved, but encoding and decoding complexity increases
Solution Approach 1:
The invention uses a single universal channel code that serves multiple functions by partitioning it into subcodes. Instead of employing multiple different codes, one code structure is designed to handle all rate allocation requirements through its subcode partitions. This universal approach maintains low complexity while achieving arbitrary rate allocation, as the same decoding algorithm can be applied to all subcodes.
3Device complexity
If a single code is used for joint decoding of multiple sources, then decoding complexity is reduced, but the ability to achieve arbitrary rate allocation among encoders is limited
Solution Approach 1:
The single channel code is segmented into multiple subcodes through partitioning the generator matrix. Each subcode maintains the structure of the original code, allowing the use of the same low-complexity decoding algorithm. The segmentation enables arbitrary rate allocation because different numbers of subcode bits can be transmitted by different encoders, while the joint decoder processes all received bits using the unified code structure.
Data Source
AI summary
System and method for designing Slepian-Wolf codes by channel code partitioning. A generator matrix is partitioned to generate a plurality of sub-matrices corresponding respectively to a plurality of correlated data sources. The partitioning is performed in accordance with a rate allocation among the plurality of correlated data sources. A corresponding plurality of parity matrices are generated based respectively on the sub-matrices, where each parity matrix is useable to encode data from a respective one of the correlated data sources.