Adjusted Min-Sum Decoding for Low-Complexity LDPC and Turbo Codes
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Solution Overview
Problem
Current decoding algorithms for LDPC and Turbo codes, such as BCJR and Sum-product decoders, are complex and not easily implementable, leading to degraded performance at lower rates, especially in high-speed applications like 5G wireless communication systems.
Innovation Solution
The implementation of an adjusted minimum-sum (AdjMS) algorithm that approximates update functions and determines magnitudes of outgoing log likelihood ratios (LLRs) for efficient decoding, allowing for a unified decoder that supports both LDPC and Turbo codes with high performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional decoding algorithms (BCJR, Sum-product) are used, then decoding accuracy is maintained, but implementation complexity increases and performance degrades at lower rates
Solution Approach 1:
The patent transforms the complex sum-product decoding algorithm into a simplified adjusted minimum-sum algorithm by changing the computational parameters from full summation to minimum-based operations. This parameter transformation maintains decoding accuracy while significantly reducing implementation complexity, especially for high-speed applications like 5G wireless communication systems
Solution Approach 2:
The patent employs a simplified decoding approach that uses approximate computations instead of exact calculations, analogous to using cheaper, simpler components. The adjusted minimum-sum algorithm provides sufficient decoding performance with reduced computational resources, making it suitable for resource-constrained high-speed communication systems
2Reliability
If complex decoding algorithms are implemented, then decoding performance is maintained, but processing speed decreases
Solution Approach 1:
The patent changes the computational parameters from complex summation operations to simpler minimum-based operations, enabling faster processing while maintaining acceptable decoding performance. This parameter transformation is crucial for achieving high-speed decoding in modern wireless communication systems
Solution Approach 2:
The adjusted minimum-sum algorithm skips complex intermediate calculation steps required by traditional sum-product decoding, rushing through the essential computations more efficiently. This approach maintains decoding performance while significantly improving processing speed for high-rate LDPC code decoding
3Reliability
If traditional decoders are used for both LDPC and Turbo codes, then code-specific performance is optimized, but device complexity increases
Solution Approach 1:
The patent develops a unified adjusted minimum-sum decoding framework that can decode both LDPC and Turbo codes using the same algorithmic structure. This universal approach eliminates the need for separate complex decoders for different code types, reducing overall device complexity while maintaining code-specific performance through parameter adjustments
Data Source
AI summary
Certain aspects of the present disclosure generally relate to techniques for efficient, high-performance decoding of low-density parity check (LDPC) codes, for example, by using an adjusted minimum-sum (AdjMS) algorithm, which involves approximating an update function and determining magnitudes of outgoing log likelihood ratios (LLRs). Similar techniques may also be used for decoding turbo codes. Other aspects, embodiments, and features (such as encoding technique) are also claimed and described.