Detection of Burst Users and Symbols for Grant-Free Communication in the Presence of Massive Connected Users

Yuanchen Wang, Xu Zhu*, Eng Gee Lim, Zhongxiang Wei*, Yufei Jiang, Lin Gan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

We investigate user activity detection (UAD) and symbol detection (SD) for grant-free communication in the presence of massive users that are actively connected to base station (BS), where a small portion of to-be-connected users wake up in a burst. The number of effective interfering connected users is reduced to only one, by applying a preconditioning matrix to the received signals from multiple antennas at BS. Subsequently, an iterative UAD and SD scheme is applied, where the priori information about the remaining interfering user is exploited and the symbols of the burst users as well as the signature connected user are simultaneously detected by iterative exchanging of the soft information of user activity and symbols. The proposed system outperforms the existing work in terms of the success rate of UAD and bit error rate.

Original languageEnglish
Pages (from-to)7973-7978
Number of pages6
JournalIEEE Transactions on Vehicular Technology
Volume71
Issue number7
DOIs
Publication statusPublished - 1 Jul 2022

Keywords

  • Compressive sensing
  • Grant-free communication
  • Interference suppression
  • Symbol detection
  • User activity detection

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