LDPC Decoder Syndrome Check for Lower Power Iterative Decoding
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Solution Overview
Problem
Traditional LDPC decoders consume high power, leading to rapid battery drain in mobile devices, despite their widespread use in error correction for noisy communications.
Innovation Solution
Implementing low-power techniques such as monitoring the channel and device conditions to enable or disable low-power syndrome checks and adjust message precision and scale factors, reducing unnecessary iterations and computations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional LDPC decoding algorithms are used, then decoding performance is maintained, but power consumption increases significantly
Solution Approach 1:
The patent applies partial action by performing syndrome checks selectively rather than executing full iterative decoding for every received vector. When syndrome checks pass, the system accepts the received vector without further processing. This partial execution approach maintains decoding reliability while significantly reducing power consumption for vectors that don't require full decoding iterations.
Solution Approach 2:
The patent implements preliminary action through early syndrome computation and validation before committing to full iterative decoding. By checking syndromes in advance and identifying valid codewords upfront, the system avoids unnecessary computational iterations, thereby reducing power consumption while preserving decoding performance for cases that truly require full processing.
2Reliability
If full iterative decoding is performed for all received vectors, then decoding accuracy is maintained, but unnecessary computations increase power consumption
Solution Approach 1:
The system performs only the necessary portion of decoding operations. By implementing early termination logic that stops iterative decoding when syndromes indicate a valid codeword, the system avoids excessive computations on vectors that have already been successfully decoded, thereby reducing energy waste while maintaining decoding accuracy.
Solution Approach 2:
The patent uses feedback from syndrome check results to control the decoding process. The syndrome validation outcome feeds back into the decision-making logic, determining whether to continue with full iterative decoding or terminate early. This feedback mechanism ensures decoding accuracy is maintained only when necessary, reducing unnecessary energy consumption.
3Reliability
If low-power syndrome checks are disabled, then normal processing ensures accurate decoding, but power consumption increases
Solution Approach 1:
The patent implements a hybrid approach where low-power syndrome checks are performed partially or selectively as a first stage, followed by full processing only when needed. This partial execution of the checking process reduces power consumption while maintaining decoding accuracy by ensuring that vectors requiring full validation receive it.
Solution Approach 2:
The decoding process is segmented into multiple stages: an initial low-power syndrome check stage, followed by a full iterative decoding stage if needed. This segmentation allows the system to use different processing intensities appropriate to each vector's requirements, reducing overall power consumption while maintaining accuracy through the staged approach.
Data Source
AI summary
This disclosure relates generally to low power data decoding, and more particularly to low power iterative decoders for data encoded with a low-density parity check (LDPC) encoder. Systems and methods are disclosed in which a low-power syndrome check may be performed in the first iteration or part of the first iteration during the process of decoding a LDPC code in an LDPC decoder. Systems and methods are also disclosed in which a control over the precision of messages sent or received and/or a change in the scaling of these messages may be implemented in the LDPC decoder. The low-power techniques described herein may reduce power consumption without a substantial decrease in performance of the applications that make use of LDPC codes or the devices that make use of low-power LDPC decoders.