Massive Connectivity with Massive MIMO - Part II: Achievable Rate Characterization

Liang Liu, Wei Yu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

55 Citations (Scopus)

Abstract

This two-part paper aims to quantify the cost of device activity detection in an uplink massive connectivity scenario with a large number of devices but device activities are sporadic. Part I of this paper shows that in an asymptotic massive multiple-input multiple-output (MIMO) regime, device activity detection can always be made perfect. Part II of this paper subsequently shows that despite the perfect device activity detection, there is nevertheless significant cost due to device detection in terms of overall achievable rate, because of the fact that nonorthogonal pilot sequences have to be used in order to accommodate the large number of potential devices, resulting in significantly larger channel estimation error as compared to conventional massive MIMO systems with orthogonal pilots. Specifically, this paper characterizes each active user's achievable rate using random matrix theory under either maximal-ratio combining (MRC) or minimum mean-squared error (MMSE) receive beamforming at the base station (BS), assuming the statistics of their estimated channels as derived in Part I. The characterization of user rate also allows the optimization of pilot sequences length. Moreover, in contrast to the conventional massive MIMO system, the MMSE beamforming is shown to achieve much higher rate than the MRC beamforming for the massive connectivity scenario under consideration. Finally, this paper illustrates the necessity of user scheduling for rate maximization when the number of active users is larger than the number of antennas at the BS.

Original languageEnglish
Pages (from-to)2947-2959
Number of pages13
JournalIEEE Transactions on Signal Processing
Volume66
Issue number11
DOIs
Publication statusPublished - 1 Jun 2018
Externally publishedYes

Keywords

  • Beamforming
  • Internet-of-Things (IoT)
  • large-system analysis
  • machine-type communications (MTC)
  • massive connectivity
  • massive multiple-input multiple-output (MIMO)
  • random matrix theory

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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