LDPC Decoder Parameter Scaling for Lower Memory Use
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Solution Overview
Problem
In communication systems employing LDPC codes, the large memory requirements and complex memory management for handling bit edge and check edge messages during iterative decoding processing pose significant challenges, particularly in high data rate applications, where traditional concatenated codes are not feasible due to latency constraints.
Innovation Solution
The implementation of operational parameter modification techniques, such as scaling, offset addition, compression, and decompression, is applied to reduce the number of bits required to represent messages in LDPC decoding, allowing for efficient management of messages and reduced memory needs without compromising coding performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional LDPC decoding is used to achieve near-capacity error correction, then coding performance is improved, but memory requirements and device complexity increase significantly
Solution Approach 1:
The patent applies parameter changes by modifying the precision of message representations during iterative decoding. Specifically, it uses operational parameter modification techniques including scaling, offset addition, compression, and decompression to reduce the number of bits required to represent bit edge and check edge messages. This allows the system to maintain near-capacity error correction performance while significantly reducing memory requirements and device complexity.
2Measurement precision
If high precision message representation is used to maintain decoding accuracy, then coding performance is improved, but memory requirements increase
Solution Approach 1:
The patent dynamically adjusts the precision parameter of message representations during the iterative decoding process. By applying scaling factors, offsets, compression functions, and decompression operations, the system can reduce the bit precision required for messages while maintaining adequate decoding accuracy. This parameter modification approach allows efficient memory utilization without sacrificing essential decoding performance.
3Reliability
If more memory is allocated for message storage, then decoding accuracy is improved, but device complexity and cost increase
Solution Approach 1:
The patent modifies the storage precision parameter for messages in memory through operational parameter modification techniques. By applying compression functions and scaling operations, the system reduces the memory precision required for storing bit edge and check edge messages while maintaining decoding accuracy. This approach simplifies memory management and reduces overall device complexity.
Solution Approach 2:
The patent uses compression and decompression operations as a form of information copying with reduced precision. Instead of storing full-precision messages in memory, the system stores compressed representations and applies decompression operations when needed, effectively creating lower-precision copies that suffice for the decoding process.
Data Source
AI summary
Operational parameter adaptable LDPC (Low Density Parity Check) decoder. A novel means is presented by which LDPC coded signal can be decoded, and any one or more operational parameters can be adjusted during the decoding processing. For example, the original information extracted from a received LDPC coded signal (e.g., log likelihood ratios (LLRs)), can be modified during (or before) the iterative decoding processing performed in accordance with decoding an LDPC coded signal. Such modification of an operational parameter can include any one or combination of scaling, compression (and expansion/decompression), adding an offset to or subtracting an offset from, scaling, rounding, and/or some other modification of an operational parameter. The bit (or variable) edge messages and/or the check edge messages can also undergo modification during decoding processing. In addition, the operational parameter modification can be selective, in that, different modification can be performed to different parameters and/or during different decoding iterations.