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Normalized Gradient Min Sum Decoding for Low Density Parity Check Codes

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Digital Technologies and Applications (ICDTA 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 668))

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Abstract

The aim of this paper is to reduce the ‘‘BER’’ and the difference between the two LDPC code families: the hard and soft one, for that, a novel hybrid “LDPC” decoding algorithm is proposed, which mixed the “Normalized Min-Sum” (NMS) and “Single Noisy Gradient Descent Bit flipping” (SNGDBF) that belongs to the soft and hard decision decoding. “The Normalized Gradient Min Sum” algorithm is proposed in this paper (NGMS). The proposed algorithm gives good results in terms of correction power, it surpasses the other algorithms with a considerable gain margins at 10–5 over the “Additive White Gaussian Noise” (AWGN) channel, according to the simulations. In addition, the suggested “NGMS” and “NMS” have the same level of decoding complexity.

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Correspondence to Hajar El Ouakili .

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El Ouakili, H., Ghzaoui, M.E., Jamil, M.O., Qjidaa, H., Alami, R.E. (2023). Normalized Gradient Min Sum Decoding for Low Density Parity Check Codes. In: Motahhir, S., Bossoufi, B. (eds) Digital Technologies and Applications. ICDTA 2023. Lecture Notes in Networks and Systems, vol 668. Springer, Cham. https://doi.org/10.1007/978-3-031-29857-8_54

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