MMSE Detection for 1-Bit Quantized Massive MIMO with Imperfect Channel Estimation

Asmaa Abdallah; Mohammad M. Mansour; Ali Chehab; Louay M.A. Jalloul

doi:10.1109/SPAWC.2018.8445780

MMSE Detection for 1-Bit Quantized Massive MIMO with Imperfect Channel Estimation

Asmaa Abdallah, Mohammad M. Mansour, Ali Chehab, Louay M.A. Jalloul

Computer, Electrical and Mathematical Sciences and Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

In this paper, we study the uplink achievable rate by a massive multiple-input multiple-output (MIMO) system in which the base station is equipped with a large number of 1-bit analog-to-digital converters (ADCs). We propose a linear minimum mean-squared error (MMSE)-based detector that accounts for the non-linearity effects of the 1-bit quantization as well as for channel estimation error. An analytical framework that derives the achievable rate of the MMSE-based detector in a massive MIMO configuration under the assumption of 1-bit quantized ADCs and channel estimation error is presented. We compare the achievable rates of a massive MIMO system using a 1-bit ADC and a linear detector against a conventional MIMO system with higher-order modulation and near maximum likelihood (ML) detection. We show that in the low signal-to-noise ratio (SNR) regime with channel estimation error, the quantized massive MIMO system can outperform the conventional large MIMO system; however for high SNR, the conventional MIMO system with a near ML detector can outperform the quantized massive MIMO system.

Original language	English (US)
Title of host publication	2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Print)	9781538635124
DOIs	https://doi.org/10.1109/SPAWC.2018.8445780
State	Published - Aug 24 2018
Event	19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018 - Kalamata, Greece Duration: Jun 25 2018 → Jun 28 2018

Publication series

Name	IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
Volume	2018-June

Conference

Conference	19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018
Country/Territory	Greece
City	Kalamata
Period	06/25/18 → 06/28/18

Keywords

1-bit quantization
channel estimation
Massive MIMO communications
MMSE detection
throughput

ASJC Scopus subject areas

Electrical and Electronic Engineering
Computer Science Applications
Information Systems

Access to Document

10.1109/SPAWC.2018.8445780

Cite this

Abdallah, A., Mansour, M. M., Chehab, A., & Jalloul, L. M. A. (2018). MMSE Detection for 1-Bit Quantized Massive MIMO with Imperfect Channel Estimation. In 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018 Article 8445780 (IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC; Vol. 2018-June). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SPAWC.2018.8445780

Abdallah, Asmaa ; Mansour, Mohammad M. ; Chehab, Ali et al. / MMSE Detection for 1-Bit Quantized Massive MIMO with Imperfect Channel Estimation. 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. (IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC).

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title = "MMSE Detection for 1-Bit Quantized Massive MIMO with Imperfect Channel Estimation",

abstract = "In this paper, we study the uplink achievable rate by a massive multiple-input multiple-output (MIMO) system in which the base station is equipped with a large number of 1-bit analog-to-digital converters (ADCs). We propose a linear minimum mean-squared error (MMSE)-based detector that accounts for the non-linearity effects of the 1-bit quantization as well as for channel estimation error. An analytical framework that derives the achievable rate of the MMSE-based detector in a massive MIMO configuration under the assumption of 1-bit quantized ADCs and channel estimation error is presented. We compare the achievable rates of a massive MIMO system using a 1-bit ADC and a linear detector against a conventional MIMO system with higher-order modulation and near maximum likelihood (ML) detection. We show that in the low signal-to-noise ratio (SNR) regime with channel estimation error, the quantized massive MIMO system can outperform the conventional large MIMO system; however for high SNR, the conventional MIMO system with a near ML detector can outperform the quantized massive MIMO system.",

keywords = "1-bit quantization, channel estimation, Massive MIMO communications, MMSE detection, throughput",

author = "Asmaa Abdallah and Mansour, {Mohammad M.} and Ali Chehab and Jalloul, {Louay M.A.}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018 ; Conference date: 25-06-2018 Through 28-06-2018",

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Abdallah, A, Mansour, MM, Chehab, A & Jalloul, LMA 2018, MMSE Detection for 1-Bit Quantized Massive MIMO with Imperfect Channel Estimation. in 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018., 8445780, IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC, vol. 2018-June, Institute of Electrical and Electronics Engineers Inc., 19th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018, Kalamata, Greece, 06/25/18. https://doi.org/10.1109/SPAWC.2018.8445780

MMSE Detection for 1-Bit Quantized Massive MIMO with Imperfect Channel Estimation. / Abdallah, Asmaa; Mansour, Mohammad M.; Chehab, Ali et al.
2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 8445780 (IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC; Vol. 2018-June).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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PY - 2018/8/24

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N2 - In this paper, we study the uplink achievable rate by a massive multiple-input multiple-output (MIMO) system in which the base station is equipped with a large number of 1-bit analog-to-digital converters (ADCs). We propose a linear minimum mean-squared error (MMSE)-based detector that accounts for the non-linearity effects of the 1-bit quantization as well as for channel estimation error. An analytical framework that derives the achievable rate of the MMSE-based detector in a massive MIMO configuration under the assumption of 1-bit quantized ADCs and channel estimation error is presented. We compare the achievable rates of a massive MIMO system using a 1-bit ADC and a linear detector against a conventional MIMO system with higher-order modulation and near maximum likelihood (ML) detection. We show that in the low signal-to-noise ratio (SNR) regime with channel estimation error, the quantized massive MIMO system can outperform the conventional large MIMO system; however for high SNR, the conventional MIMO system with a near ML detector can outperform the quantized massive MIMO system.

AB - In this paper, we study the uplink achievable rate by a massive multiple-input multiple-output (MIMO) system in which the base station is equipped with a large number of 1-bit analog-to-digital converters (ADCs). We propose a linear minimum mean-squared error (MMSE)-based detector that accounts for the non-linearity effects of the 1-bit quantization as well as for channel estimation error. An analytical framework that derives the achievable rate of the MMSE-based detector in a massive MIMO configuration under the assumption of 1-bit quantized ADCs and channel estimation error is presented. We compare the achievable rates of a massive MIMO system using a 1-bit ADC and a linear detector against a conventional MIMO system with higher-order modulation and near maximum likelihood (ML) detection. We show that in the low signal-to-noise ratio (SNR) regime with channel estimation error, the quantized massive MIMO system can outperform the conventional large MIMO system; however for high SNR, the conventional MIMO system with a near ML detector can outperform the quantized massive MIMO system.

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T3 - IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC

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PB - Institute of Electrical and Electronics Engineers Inc.

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Y2 - 25 June 2018 through 28 June 2018

ER -

Abdallah A, Mansour MM, Chehab A, Jalloul LMA. MMSE Detection for 1-Bit Quantized Massive MIMO with Imperfect Channel Estimation. In 2018 IEEE 19th International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2018. Institute of Electrical and Electronics Engineers Inc. 2018. 8445780. (IEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC). doi: 10.1109/SPAWC.2018.8445780

MMSE Detection for 1-Bit Quantized Massive MIMO with Imperfect Channel Estimation

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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