University of Oulu

I. Atzeni and A. Tölli, "Channel Estimation and Data Detection Analysis of Massive MIMO with 1-Bit ADCs," in IEEE Transactions on Wireless Communications, doi: 10.1109/TWC.2021.3124709

Channel estimation and data detection analysis of massive MIMO with 1-Bit ADCs

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Author: Atzeni, Italo1; Tölli, Antti1
Organizations: 1Centre for Wireless Communications, University of Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 3.7 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2021121761603
Language: English
Published: Institute of Electrical and Electronics Engineers, 2021
Publish Date: 2021-12-17
Description:

Abstract

We present an analytical framework for the channel estimation and the data detection in massive multiple-input multiple-output uplink systems with 1-bit analog-to-digital converters (ADCs) and i.i.d. Rayleigh fading. First, we provide closed-form expressions of the mean squared error (MSE) of the channel estimation considering the state-of-the-art linear minimum MSE estimator and the class of scaled least-squares estimators. For the data detection, we provide closed-form expressions of the expected value and the variance of the estimated symbols when maximum ratio combining is adopted, which can be exploited to efficiently implement minimum distance detection and, potentially, to design the set of transmit symbols. Our analytical findings explicitly depend on key system parameters such as the signal-to-noise ratio (SNR), the number of user equipments, and the pilot length, thus enabling a precise characterization of the performance of the channel estimation and the data detection with 1-bit ADCs. The proposed analysis highlights a fundamental SNR trade-off, according to which operating at the right noise level significantly enhances the system performance.

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Series: IEEE transactions on wireless communications
ISSN: 1536-1276
ISSN-E: 1558-2248
ISSN-L: 1536-1276
Issue: Early access
DOI: 10.1109/TWC.2021.3124709
OADOI: https://oadoi.org/10.1109/TWC.2021.3124709
Type of Publication: A1 Journal article – refereed
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
Funding: The work of A. Tölli was supported by the Academy of Finland (318927 6Genesis Flagship and 319059 CCCWEE). Part of this work has been presented at IEEE SPAWC 2021, Lucca, Italy, Sept. 2021.
Copyright information: This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/.
  https://creativecommons.org/licenses/by/4.0/