Parallel LDPC Decoding for Correlated Data Bit Groups
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Solution Overview
Problem
Conventional communication systems using LDPC codes face inefficiencies in error correction due to assuming independent input data bits, which can lead to suboptimal performance when dealing with correlated data, and typical hardware systems lack the capability to concurrently correct errors across multiple groups of correlated data bits.
Innovation Solution
A parallel iterative decoding system that groups correlated data bits and generates soft information using a channel detection module, with computation and decoding modules working in parallel to produce estimates and feedback signals, allowing for concurrent error correction across multiple groups of correlated data bits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional LDPC decoding assumes independent input data bits, then the decoding process is simpler, but the error correction performance deteriorates when dealing with correlated data
Solution Approach 1:
The patent segments correlated data bits into multiple groups and processes each group separately through parallel decoding channels. This segmentation allows the system to handle correlated data effectively while maintaining manageable complexity by dividing the problem into independent sub-problems that can be solved concurrently.
Solution Approach 2:
The patent introduces a new dimension of processing by creating multiple parallel decoding channels that operate simultaneously on different groups of correlated data bits. This dimensional expansion from single-channel sequential processing to multi-channel parallel processing resolves the contradiction by enabling correlated data handling without proportionally increasing overall system complexity.
2Device complexity
If typical hardware systems process data bits sequentially, then the device complexity is lower, but the productivity deteriorates due to inability to concurrently correct errors across multiple groups
Solution Approach 1:
The hardware system is segmented into multiple parallel decoding channels, each capable of independently processing a group of correlated data bits. This segmentation enables concurrent error correction across multiple groups, significantly improving productivity while keeping each individual channel relatively simple in structure.
Solution Approach 2:
The patent merges multiple parallel decoding channels into a unified hardware architecture that processes multiple groups of correlated data bits simultaneously. By combining several simple processing units into a parallel system, the architecture achieves high productivity without requiring each individual unit to be overly complex.
3Reliability
If parallel iterative decoding is implemented to handle correlated data, then the error correction performance improves, but the use of energy increases due to multiple concurrent processing operations
Solution Approach 1:
The parallel iterative decoding system is segmented into multiple independent channels that process different groups of correlated data bits simultaneously. This segmentation allows the energy consumption to be distributed across multiple smaller processing units rather than concentrated in a single complex processor, making the overall energy usage more efficient while maintaining high decoding performance.
Solution Approach 2:
Each parallel decoding channel operates independently and autonomously, performing self-service error correction on its assigned group of correlated data bits. This self-service approach eliminates the need for complex coordination and control mechanisms that would otherwise increase energy consumption, allowing the system to achieve high performance with reduced overall energy usage.
Data Source
AI summary
A decoder for a communication system includes a channel detection module configured to receive initial estimates of respective code words, wherein the initial estimates of the respective code words correspond to a signal received via a communication channel, arrange the initial estimates of the respective code words into a plurality of groups, and generate probability information associated with selected data bits of the respective code words in the plurality of groups, wherein the probability information indicates probabilities of decoding decisions of the selected data bits. A computation module is configured to generate bit estimations for each of the selected data bits based on the probability information and feedback information. A decoding module is configured to selectively generate, the feedback information and an estimate signal corresponding to the respective code words.