A Covariance-based User Activity Detection and Channel Estimation Approach with Novel Pilot Design

Lei Cheng, Liang Liu, Shuguang Cui

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

2 Citations (Scopus)

Abstract

This paper studies the massive machine-Type communications (mMTC) for the future Internet of Things (IoT) applications. Building upon the fact that the covariance matrix of the received signal can be accurately estimated in the spatial domain if the base station (BS) is equipped with a massive number of antennas, we propose a covariance-based device activity detection and channel estimation strategy in a massive MIMO (multiple-input multiple-output) aided mMTC system. For this strategy, a novel approach for the pilot sequence design is first provided, where the pilot of each device is merely determined by a unique phase parameter. Then, by estimating the phase parameters of the active pilot sequences that contribute to the received covariance matrix, an efficient algorithm is proposed to detect the active devices without the prior information about the total number of active devices. At last, given the estimation of active devices, channel estimation is conducted based on the conventional minimum mean-squared error (MMSE) approach. It is worth noting that our proposed strategy is able to obtain all the results in closed-forms, and is thus of much lower complexity compared to the existing strategies that are based on iterative algorithms for device detection and channel estimation.

Original languageEnglish
Title of host publication2020 IEEE 21st International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728154787
DOIs
Publication statusPublished - May 2020
Event21st IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2020 - Atlanta, United States
Duration: 26 May 202029 May 2020

Publication series

NameIEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
Volume2020-May

Conference

Conference21st IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2020
Country/TerritoryUnited States
CityAtlanta
Period26/05/2029/05/20

Keywords

  • Covariance matrices
  • Channel estimation
  • Partial transmit sequences
  • MIMO communication
  • Compressed sensing
  • Antennas
  • Wireless communication

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Information Systems

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