LDPC Decoder Convergence Gating for Lower Power Decoding
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Solution Overview
Problem
Current LDPC decoders experience high power consumption due to redundant operations during the iterative decoding process, which do not contribute to convergence, leading to inefficiencies in error correction performance.
Innovation Solution
Implementing a check node convergence tester to disable redundant operations and gate off processing elements when check nodes have converged, reducing power consumption and optimizing processing by only performing necessary decoding operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the iterative decoding process continues until convergence, then error correction performance is improved, but power consumption increases due to redundant operations
Solution Approach 1:
The patent applies partial action by performing decoding operations only on check nodes that have not yet converged. The convergence tester identifies which check nodes require processing, and the decoder performs operations only on those specific nodes rather than all check nodes in each iteration. This reduces redundant operations while maintaining error correction performance.
Solution Approach 2:
The patent implements dynamic adaptation by continuously monitoring the convergence state of check nodes and adjusting the decoding process accordingly. The convergence tester dynamically identifies converged check nodes, and the decoder dynamically adjusts which operations are performed based on this real-time information, transitioning from static full-iteration processing to dynamic selective processing.
2Reliability
If all check nodes are processed in each iteration, then convergence is ensured, but processing throughput decreases due to redundant operations
Solution Approach 1:
The patent performs partial processing by focusing computational resources only on check nodes that have not converged. The convergence tester identifies the subset of active check nodes, and the decoder processes only those nodes in each iteration, eliminating redundant processing of converged nodes while ensuring convergence is achieved for all necessary nodes.
Solution Approach 2:
The patent segments the set of check nodes into converged and non-converged subsets. The convergence tester divides the check node processing task by identifying which nodes require attention, and the decoder segments its operations to process only the non-converged subset, improving throughput by avoiding unnecessary processing of the converged subset.
3Use of energy by moving object
If the number of iterations is reduced, then power consumption decreases, but error correction performance may degrade
Solution Approach 1:
The patent achieves better power efficiency by performing partial operations on fewer check nodes per iteration rather than reducing the total number of iterations. This maintains the iterative process until convergence while reducing redundant operations, thereby preserving error correction performance while lowering power consumption.
Solution Approach 2:
The convergence tester enables the decoding system to self-regulate by automatically identifying when check nodes have converged and signaling the decoder to stop processing those nodes. This self-service mechanism ensures that the system performs exactly the necessary operations for convergence without excessive processing, optimizing the balance between power consumption and performance.
4Use of energy by moving object
If redundant operations are eliminated, then power consumption is reduced, but implementation complexity increases
Solution Approach 1:
The convergence tester acts as an intermediary component that bridges the decoder and the check nodes. It monitors the convergence state and provides control signals to the decoder, enabling selective processing. This intermediary layer manages the complexity of tracking convergence states while keeping the core decoding logic relatively simple and modular.
Solution Approach 2:
The patent implements a feedback mechanism where the convergence tester continuously monitors the state of check nodes and feeds this information back to the decoder. This feedback loop enables the system to adapt its processing based on actual convergence progress, reducing redundant operations while maintaining a relatively simple implementation through straightforward convergence checking logic.
Data Source
AI summary
A Forward Error Correction (FEC) decoder is provided, for example including a Layered Low Density Parity Check (LDPC) component. In an implementation, power consumption of the LDPC decoder is minimized with minimal to no impact on the error correction performance. This is achieved, in an implementation, by partially or fully eliminating redundant operations in the iterative process.