Abstract
Low-density parity-check (LDPC) codes, invented in the 1960s by Gallegar, are a significant topic in coding theory and have large number of practical applications in various scientific domains. Different variants of LDPC codes are developed in the literature which are having better performing encoding as well as decoding procedures. The design of these LDPC coding algorithms is in such a way that it can get back the original message codeword even in the case of massive amount of noise in the communication channel or missing some codeword bits. Therefore, LDPC codes are perfect candidates for real-time applications. This paper presents an efficient message passing procedure to perform the decoding of LDPC codes. The proposed procedure results in the reduction of computational complexity. This procedure exploits hard decision decoding method. The experimental simulation is also performed using additive white Gaussian noise (AWGN) channel through which we obtained different bit error rate (BER) values corresponding to different threshold and signal-to-noise ratio (SNR) values. The adaptability of this simulation is in practical usage in wireless sensor network scenario. In the experiment results, it is observed that with the increase of SNR values in the 1–30 db, BER values are decreased.
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Naidu, A.S., Tentu, A.N., Singh, A. (2022). Reduced Complexity of LDPC Codes using Hard Decision Decoder. In: Pandian, A.P., Fernando, X., Haoxiang, W. (eds) Computer Networks, Big Data and IoT. Lecture Notes on Data Engineering and Communications Technologies, vol 117. Springer, Singapore. https://doi.org/10.1007/978-981-19-0898-9_29
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DOI: https://doi.org/10.1007/978-981-19-0898-9_29
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