A Compressive Sensing-Based Active User and Symbol Detection Technique for Massive Machine-Type Communications

Byeong Kook Jeong, Byonghyo Shim, Kwang Bok Lee

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

1 Citation (Scopus)

Abstract

In massive machine-type communication (mMTC) systems, a large number of machine-type devices sporadically transmit small packets with low rates. By exploiting the sporadic activity of machine-type devices, we can cast the detection problem as the compressive sensing-based multi-user detection (CS-MUD). In this paper, we propose a novel CS-MUD algorithm for the active user and symbol detection based on a maximum a posteriori probability (MAP) criterion. By exchanging extrinsic information between active user detector and symbol detector, the proposed algorithm improves the performance of active user detection and the reliability of symbol estimate. Numerical simulations demonstrate that the proposed algorithm achieves outstanding MUD performance.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6623-6627
Number of pages5
Volume2018-April
ISBN (Print)9781538646588
DOIs
Publication statusPublished - 2018 Sep 10
Externally publishedYes
Event2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Calgary, Canada
Duration: 2018 Apr 152018 Apr 20

Other

Other2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018
CountryCanada
CityCalgary
Period18/4/1518/4/20

Keywords

  • Compressive sensing-based multi-user detection
  • Massive machine-type communications
  • Maximum a posteriori probability

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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  • Cite this

    Jeong, B. K., Shim, B., & Lee, K. B. (2018). A Compressive Sensing-Based Active User and Symbol Detection Technique for Massive Machine-Type Communications. In 2018 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2018 - Proceedings (Vol. 2018-April, pp. 6623-6627). [8462195] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASSP.2018.8462195