Multi-User Detections for Sparse Code Multiple Access System

Joonki Kim, Daesik Hong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This paper proposes a new multi-user detection scheme for sparse code multiple access (SCMA) system in grant-free scenario. SCMA systems use a message passing algorithm which considers all user equipments (UEs) to be active. However, in a practical system, UEs do not always request resources. A multi-user detection procedure enables the decoder to mitigate interference from proper active UEs and to ignore the signal from inactive UEs. Therefore, we propose a multi-user detection scheme for SCMA system. The simulation results present that the proposed SCMA receiver structure achieves a remarkable enhancement in false alarm probability, miss detection probability.

Original languageEnglish
Title of host publication2018 IEEE 88th Vehicular Technology Conference, VTC-Fall 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538663585
DOIs
Publication statusPublished - 2018 Jul 2
Event88th IEEE Vehicular Technology Conference, VTC-Fall 2018 - Chicago, United States
Duration: 2018 Aug 272018 Aug 30

Publication series

NameIEEE Vehicular Technology Conference
Volume2018-August
ISSN (Print)1550-2252

Conference

Conference88th IEEE Vehicular Technology Conference, VTC-Fall 2018
Country/TerritoryUnited States
CityChicago
Period18/8/2718/8/30

Bibliographical note

Funding Information:
This work was supported in part by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2018R1A2A1A05021029) and by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIP) (No. 2016-0-00181, Development on the core technologies of transmission, modulation, and coding with low-power and low-complexity for massive connectivity in the IoT environment).

Publisher Copyright:
© 2018 IEEE.

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

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