On LDPC Code Based Massive Random-Access Scheme for the Gaussian Multiple Access Channel

Anton Glebov, Luiza Medova, Pavel Rybin, Alexey Frolov

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    9 Citations (Scopus)

    Abstract

    This paper deals with the problem of massive random access for Gaussian multiple access channel (MAC). We continue to investigate the coding scheme for Gaussian MAC proposed by A. Vem et al. in 2017. The proposed scheme consists of four parts: (i) the data transmission is partitioned into time slots; (ii) the data, transmitted in each slot, is split into two parts, the first one set an interleaver of the low-density parity-check (LDPC) type code and is encoded by spreading sequence or codewords that are designed to be decoded by compressed sensing type decoding; (iii) the another part of transmitted data is encoded by LDPC type code and decoded using a joint message passing decoding algorithm designed for the T-user binary input Gaussian MAC; (iv) users repeat their codeword in multiple slots. In this paper we are concentrated on the third part of considered scheme. We generalized the PEXIT charts to optimize the protograph of LDPC code for Gaussian MAC. The simulation results, obtained at the end of the paper, were analyzed and compared with obtained theoretical bounds and thresholds. Obtained simulation results shows that proposed LDPC code constructions have better performance under joint decoding algorithm over Gaussian MAC than LDPC codes considered by A. Vem et al. in 2017, that leads to the better performance of overall transmission system.

    Original languageEnglish
    Title of host publicationInternet of Things, Smart Spaces, and Next Generation Networks and Systems - 18th International Conference, NEW2AN 2018, and 11th Conference, ruSMART 2018, Proceedings
    EditorsSergey Balandin, Olga Galinina, Sergey Andreev, Yevgeni Koucheryavy
    PublisherSpringer Verlag
    Pages162-171
    Number of pages10
    ISBN (Print)9783030011673
    DOIs
    Publication statusPublished - 2018
    Event18th International Conference on Next Generation Teletraffic and Wired/Wireless Advanced Networks and Systems, NEW2AN 2018 and 11th Conference on Internet of Things and Smart Spaces, ruSMART 2018 - St. Petersburg, Russian Federation
    Duration: 27 Aug 201829 Aug 2018

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume11118 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference18th International Conference on Next Generation Teletraffic and Wired/Wireless Advanced Networks and Systems, NEW2AN 2018 and 11th Conference on Internet of Things and Smart Spaces, ruSMART 2018
    Country/TerritoryRussian Federation
    CitySt. Petersburg
    Period27/08/1829/08/18

    Keywords

    • Gaussian MAC
    • LDPC code
    • Massive random-access
    • NOMA
    • PEXIT charts

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