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대한전자공학회 학술대회

A Node Monitoring Algorithm for Efficient LDPC Decoding

주경삼, 양석, 서희종

Published Jun 1, 2008• 2 citations
OpenAlex

Abstract

In this paper, we propose an efficient algorithm for reducing the complexity of LDPC code decoding by using node monitoring (NM). This NM algorithm is based on a new node-threshold method, and the message passing algorithm. This algorithm was simulated in order to verify its efficiency. Simulation results show that the complexity of our NM algorithm is improved to about 10%, compared with well-known methods.

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In this paper, we propose an efficient algorithm for reducing the complexity of LDPC code decoding by using node monitoring (NM). This NM algorithm is based on a new node-threshold method, and the message passing algorithm. This algorithm was simulated in order to verify its efficiency. Simulation results show that the complexity of our NM algorithm is improved to about 10%, compared with well-known methods.
In this paper, we propose an efficient algorithm for reducing the complexity of LDPC code decoding by using node monitoring (NM) and Piecewise Linear Function Approximation (NP). This NM algorithm is based on a new node-threshold method, and the message passing algorithm. Piecewise linear function approximation is used to reduce the complexity for more. This algorithm was simulated in order to verify its efficiency. Simulation results show that the complexity of our NM algorithm is reduced to about 20%, compared with thoes of well-known method.
본 논문에서는 노드 모니터링(NM)과 Piecewise Linear Function Approximation(: NP)을 사용하여 LDPC 디코딩 알고리듬의 계산복잡도를 감소시키는 알고리듬을 제안한다. 이 알고리듬은 기존의 알고리듬보다도 더 효율적이다. 제안된 알고리즘이 기존의 방법보다도 개선되었다는 것을 확인하기 위해서 모의실험을 하였다. 실험결과, 제안된 알고리즘의 계산은 기존의 방법에 비해 약 20 % 향상되었음을 확인하였다. In this paper, we proposed an efficient algorithm using Node monitoring (NM) and Piecewise Linear Function Approximation(: NP) for reducing the complexity of LDPC code decoding. Proposed NM algorithm is based on a new node-threshold method together with message passing algorithm. Piecewise linear function approximation is used to reduce the complexity of the algorithm. This new algorithm was simulated in order to verify its efficiency. Complexity of our new NM algorithm is improved to about 20% compared with well-known methods according to simulation results.
This paper presents a low complexity non-binary LDPC decoding algorithm,whose complexity can be reduced in the following two ways.First,a new truncation scheme is presented to define the processing/non-processing check node subsets.The check nodes with relatively high reliability are not required to be processed,which can reduce the complexity.Second,for the check nodes in the processing subset,we further present a k-order message truncation for the states and branches of the check node Trellis.In the decoding iterations,only those live states/branches are involved in the message updating process,which can further reduce the computational loads at check nodes.Simulation results show that the presented algorithm performs very closely to several existing improved EMS decoding algorithms,but it has the lowest complexity when decoding the non-binary LDPC codes constructed both in low/high order fields.%
In this paper, we propose an efficient message passing architecture for permutation matrices based LDPC code decoders. Min-sum algorithm is reformulated to facilitate significant reduction of routing complexity and memory usage. For a (2048, 1723) (6, 32) LDPC code with 4-bit quantization, 54% outgoing wires per variable node unit and 90% outgoing wires per check node unit can be saved. To further reduce hardware complexity, an optimized nonuniform quantization scheme using only 3 bits to represent each message has been investigated. The simulation result shows that it has only 0.25dB performance loss from the floating-point SPA
As for the sum-product decoding algorithm of LDPC codes,a new kind of difference-based decoding method is proposed.The main idea about it is that the messages passed on the bipartite graph of LDPC are based on the probability differences,and the renewal of both check nodes and message nodes is carried out on the special addition domain.As for the renewal of check nodes,some differences possessing the minimum absolute values can be selected to further reduce the complexity of computation.In contrast with the traditional LLR-based decoding method,the proposed method has much lower complexity,while it has no obvious loss of performance and convergence.