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Performance of Systematic Convolutional Low Density Generator Matrix Codes over Rayleigh Fading Channels with Impulsive Noise

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Space Information Networks (SINC 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 972))

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Abstract

We investigate the systematic convolutional low density generator matrix (SC-LDGM) codes over Rayleigh fading channels with symmetric alpha-stable (S\(\alpha \)S) impulsive noise. The performance is analyzed by deriving a lower bound based on an equivalent genie-aided (GA) system. Numerical simulations show that the SC-LDGM codes can achieve a significant gain compared to the convolutional codes over Rayleigh fading channels with impulsive noise. Numerical results also show that the performance of the SC-LDGM codes can be around one dB away from Shannon limits at the bit-error rate (BER) of \(10^{-5}\) and matches well with the GA lower bound in the low BER region.

X. Ma—This work was supported by the National Natural Science Foundation of China (No. 91438101).

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Authors and Affiliations

  1. School of Data and Computer Science, Sun Yat-sen University, Guangzhou, 510006, China

    Meiying Ji & Xiao Ma

  2. School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, 510006, China

    Shengxiao Chen

  3. Guangdong Key Laboratory of Information Security Technology, Sun Yat-sen University, Guangzhou, 510006, China

    Meiying Ji, Shengxiao Chen & Xiao Ma

Authors
  1. Meiying Ji
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  2. Shengxiao Chen
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  3. Xiao Ma
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Corresponding author

Correspondence to Xiao Ma .

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Editors and Affiliations

  1. PLA Academy of Military Science, Beijing, China

    Quan Yu

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Ji, M., Chen, S., Ma, X. (2019). Performance of Systematic Convolutional Low Density Generator Matrix Codes over Rayleigh Fading Channels with Impulsive Noise. In: Yu, Q. (eds) Space Information Networks. SINC 2018. Communications in Computer and Information Science, vol 972. Springer, Singapore. https://doi.org/10.1007/978-981-13-5937-8_11

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  • DOI: https://doi.org/10.1007/978-981-13-5937-8_11

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-5936-1

  • Online ISBN: 978-981-13-5937-8

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