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author:

He, Yuyi (He, Yuyi.) [1] | Lv, Liang (Lv, Liang.) [2] | Fang, Yi (Fang, Yi.) [3] | Yin, Liuguo (Yin, Liuguo.) [4] | Chen, Pingping (Chen, Pingping.) [5]

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EI

Abstract:

In this letter, we propose a novel neural network-aided receiver, called extrinsic-information chaos network-aided iterative decoding (EICNet-ID) receiver, for protograph low-density parity-check (PLDPC)-coded M -ary differential chaos shift keying (DCSK) systems. Specifically, the EICNet structure captures the correlation features between the chaotic sequences of the received M -ary DCSK symbol to obtain more accurate a-priori log-likelihood ratio (LLR) without requiring the channel state information (CSI). Moreover, the EICNet structure considers both the received symbol and its a-posteriori probabilities, allowing the extrinsic information provided by the PLDPC decoder to update network input and enhance error performance. Both simulation and analysis results demonstrate that the proposed EICNet-ID receiver exhibits desirable performance compared to the existing counterparts. © 1997-2012 IEEE.

Keyword:

Chaos control Health risks Iterative decoding Network coding Risk assessment Turbo codes

Community:

  • [ 1 ] [He, Yuyi]Guangdong University of Technology, School of Information Engineering, Guangzhou; 510006, China
  • [ 2 ] [Lv, Liang]Guangdong University of Technology, School of Information Engineering, Guangzhou; 510006, China
  • [ 3 ] [Fang, Yi]Guangdong University of Technology, School of Information Engineering, Guangzhou; 510006, China
  • [ 4 ] [Yin, Liuguo]Tsinghua University, School of Information Science and Technology, Beijing; 100084, China
  • [ 5 ] [Chen, Pingping]Fuzhou University, Department of Electronic Information, Fuzhou; 350116, China

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Source :

IEEE Communications Letters

ISSN: 1089-7798

Year: 2024

Issue: 12

Volume: 28

Page: 2700-2704

3 . 7 0 0

JCR@2023

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ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 1

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