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SiPS ... design and implementation - IEEE Workshop on Signal Processing Systems

New simplified sum-product algorithm for low complexity LDPC decoding

Myung Hun Lee, Jae Hee Han, Myung Hoon Sunwoo

Published Oct 1, 2008• 10 citations
Publisher

Abstract

This paper proposes new simplified sum-product (SSP) decoding algorithm to improve BER performance for low-density parity-check codes. The proposed SSP algorithm can replace multiplications and divisions with additions and subtractions without extra computations. In addition, the proposed SSP algorithm can simplify both the ln[tanh(x)] and exp[tanh-1(x)] by using two quantization tables which can reduce tremendous computational complexity. Moreover, the simulation results show that the proposed SSP algorithm can improve about 0.3~0.8 dB of BER performance compared with the existing modified sum-product algorithm.

DOI
10.1109/sips.2008.4671738

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This paper proposes new simplified sum-product (SSP) decoding algorithm to improve BER performance for low-density parity-check codes. The proposed SSP algorithm can replace multiplications and divisions with additions and subtractions without extra computations. In addition, the proposed SSP algorithm can simplify both the ln[tanh(x)] and exp[tanh-1(x)] by using two quantization tables which can reduce tremendous computational complexity. Moreover, the simulation results show that the proposed SSP algorithm can improve about 0.3~0.8 dB of BER performance compared with the existing modified sum-product algorithm.
This paper proposes new simplified sum-product (SSP) decoding algorithm to improve BER performance for low-density parity-check codes. The proposed SSP algorithm can replace multiplications and divisions with additions and subtractions without extra computations. In addition, the proposed SSP algorithm can simplify both the In[tanh(x)] and tanh-1 [exp(x)] by using two quantization tables which can reduce tremendous computational complexity. Moreover, the simulation results show that the proposed SSP algorithm can improve about of BER performance compared with the existing modified sum-product algorithms.
This paper proposes the simplified sum-product (SSP) decoding algorithm to improve BER performance for low-density parity-check codes (LDPC). The sum-product algorithm achieves the highest BER performance among the LDPC decoding algorithms. However, based on the hyperbolic tangent and inverse hyperbolic tangent functions for the check node updates, the sum-product (SP) algorithm requires high computational complexity. To reduce computational complexity, the proposed SSP algorithm adopts a piecewise linear approximation, the logarithmic and exponential functions, which can replace multiplications and divisions with additions and subtractions. In addition, the proposed SSP algorithm can simplify both the ln[tanh(x)] and tanh-1[exp(x)] by using two quantization tables which can reduce tremendous computational complexity. Simulation results show that the proposed SSP algorithm can improve about 0.8 dB of bit error ratio (BER) performance compared with the modified sum-product algorithm.
This paper proposes a new sum-product algorithm to improve BER performance for low-density parity-check codes. The proposed algorithm can replace multiplications and divisions with additions and subtractions by adding the logarithmic and exponential functions. In addition, the proposed algorithm can simplify both the ln[tanh(x)] and tanh-1[exp(x)] functions by using two quantization tables which can reduce tremendous computational complexity. Moreover, the simulation results show that the proposed SP algorithm can improve maximum of 0.8 dB BER performance compared with the existing modified sumproduct algorithm.
This paper present a novel decoding scheme for low density parity check codes (LDPC) over GF(q). The scheme is a variation of the sum-product algorithm. The novel algorithm has a low complexity and reduces the number of look up table accesses necessary. Moreover, the algorithm does not compute division or multiplication, making it suitable for hardware implementation. The new algorithm has been compared with existing algorithms showing that both the BER performance and the speed of convergence are identical.
A simplified decoding algorithm for low-density parity-check (LDPC) codes over high order Galois field is proposed to reduce the complexity of traditional sum-product algorithm (SPA). There are only addition operation and comparison operation in this algorithm, without complex multiplication operation. The computation complexity of proposed algorithm is much smaller than the SPA. The signal-to-noise power ratio (SNR) isn't needed in this algorithm, so the process of SNR estimation can also be removed. The simulation results show that the bit error rate (BER) performance of proposed algorithm degrades only about 0.5 dB than the SPA, so the proposed algorithm is an efficient simplified algorithm in engineering.
In this paper, an improved low-complexity sum-product decoding algorithm is presented for low-density parity-check (LDPC) codes. In the proposed algorithm, reduction in computational complexity is achieved by utilizing fast Fourier transform (FFT) with time shift in the check node process. The improvement in the decoding performance is achieved by utilizing an optimized integer constant in the variable node process. Simulation results show that the proposed algorithm achieves an overall coding gain improvement ranging from 0.04 to 0.46 dB. Moreover, when compared with the sum-product algorithm (SPA), the proposed decoding algorithm can achieve a reduction of 42%–67% of the total number of arithmetic operations required for the decoding process.