A general framework for MIMO receivers with low-resolution quantization

Stefano Rini, Luca Barletta, Yonina C. Eldar, Elza Erkip

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The capacity of a discrete-time, multi-input multi-output (MIMO) channel with output quantization is investigated for different receiver architectures. A general framework for low-resolution quantization is proposed in which the antenna outputs are processed by analog combiners and sign quantizers are used for analog-to-digital conversion. The configuration of the analog combiners is chosen as a function of the channel realization so that the transmission rate can be maximized over the set of available configurations. To exemplify the proposed approach, four analog receiver architectures are considered: (a) sign quantization of the antenna outputs, (b) single antenna selection, (c) multiple antenna selection, and (d) linear processing of the antenna outputs. In each scenario, capacity is investigated as a function of the transmit power, the number of transmit/receive antennas and sign quantizers. In particular, it is shown that architecture (a) is sufficient to approach the optimal high signal-to-noise ratio (SNR)performance for a MIMO receiver in which the number of receive antennas is larger than the number of sign quantizers. Numerical evaluations of the average performance are presented for the case in which the channel gains are i.i.d. Gaussian distributed.

Original languageEnglish (US)
Title of host publication2017 IEEE Information Theory Workshop, ITW 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages599-603
Number of pages5
Volume2018-January
ISBN (Electronic)9781509030972
DOIs
StatePublished - Jan 31 2018
Event2017 IEEE Information Theory Workshop, ITW 2017 - Kaohsiung, Taiwan, Province of China
Duration: Nov 6 2017Nov 10 2017

Other

Other2017 IEEE Information Theory Workshop, ITW 2017
CountryTaiwan, Province of China
CityKaohsiung
Period11/6/1711/10/17

Fingerprint

Quantization
Receiver
Antenna
Antennas
Output
Analogue
Antenna Selection
Configuration
Multiple Antennas
Analog to digital conversion
Framework
Discrete-time
Signal to noise ratio
Sufficient
Scenarios
Evaluation
Processing
Architecture

Keywords

  • Analog-to-digital conversion
  • Channel output quantization
  • MIMO channel
  • One-bit quantization

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Information Systems
  • Modeling and Simulation
  • Applied Mathematics

Cite this

Rini, S., Barletta, L., Eldar, Y. C., & Erkip, E. (2018). A general framework for MIMO receivers with low-resolution quantization. In 2017 IEEE Information Theory Workshop, ITW 2017 (Vol. 2018-January, pp. 599-603). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITW.2017.8277991

A general framework for MIMO receivers with low-resolution quantization. / Rini, Stefano; Barletta, Luca; Eldar, Yonina C.; Erkip, Elza.

2017 IEEE Information Theory Workshop, ITW 2017. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. p. 599-603.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Rini, S, Barletta, L, Eldar, YC & Erkip, E 2018, A general framework for MIMO receivers with low-resolution quantization. in 2017 IEEE Information Theory Workshop, ITW 2017. vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 599-603, 2017 IEEE Information Theory Workshop, ITW 2017, Kaohsiung, Taiwan, Province of China, 11/6/17. https://doi.org/10.1109/ITW.2017.8277991
Rini S, Barletta L, Eldar YC, Erkip E. A general framework for MIMO receivers with low-resolution quantization. In 2017 IEEE Information Theory Workshop, ITW 2017. Vol. 2018-January. Institute of Electrical and Electronics Engineers Inc. 2018. p. 599-603 https://doi.org/10.1109/ITW.2017.8277991
Rini, Stefano ; Barletta, Luca ; Eldar, Yonina C. ; Erkip, Elza. / A general framework for MIMO receivers with low-resolution quantization. 2017 IEEE Information Theory Workshop, ITW 2017. Vol. 2018-January Institute of Electrical and Electronics Engineers Inc., 2018. pp. 599-603
@inproceedings{97327c002fcf46f1a08f7bbce44ba787,
title = "A general framework for MIMO receivers with low-resolution quantization",
abstract = "The capacity of a discrete-time, multi-input multi-output (MIMO) channel with output quantization is investigated for different receiver architectures. A general framework for low-resolution quantization is proposed in which the antenna outputs are processed by analog combiners and sign quantizers are used for analog-to-digital conversion. The configuration of the analog combiners is chosen as a function of the channel realization so that the transmission rate can be maximized over the set of available configurations. To exemplify the proposed approach, four analog receiver architectures are considered: (a) sign quantization of the antenna outputs, (b) single antenna selection, (c) multiple antenna selection, and (d) linear processing of the antenna outputs. In each scenario, capacity is investigated as a function of the transmit power, the number of transmit/receive antennas and sign quantizers. In particular, it is shown that architecture (a) is sufficient to approach the optimal high signal-to-noise ratio (SNR)performance for a MIMO receiver in which the number of receive antennas is larger than the number of sign quantizers. Numerical evaluations of the average performance are presented for the case in which the channel gains are i.i.d. Gaussian distributed.",
keywords = "Analog-to-digital conversion, Channel output quantization, MIMO channel, One-bit quantization",
author = "Stefano Rini and Luca Barletta and Eldar, {Yonina C.} and Elza Erkip",
year = "2018",
month = "1",
day = "31",
doi = "10.1109/ITW.2017.8277991",
language = "English (US)",
volume = "2018-January",
pages = "599--603",
booktitle = "2017 IEEE Information Theory Workshop, ITW 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - A general framework for MIMO receivers with low-resolution quantization

AU - Rini, Stefano

AU - Barletta, Luca

AU - Eldar, Yonina C.

AU - Erkip, Elza

PY - 2018/1/31

Y1 - 2018/1/31

N2 - The capacity of a discrete-time, multi-input multi-output (MIMO) channel with output quantization is investigated for different receiver architectures. A general framework for low-resolution quantization is proposed in which the antenna outputs are processed by analog combiners and sign quantizers are used for analog-to-digital conversion. The configuration of the analog combiners is chosen as a function of the channel realization so that the transmission rate can be maximized over the set of available configurations. To exemplify the proposed approach, four analog receiver architectures are considered: (a) sign quantization of the antenna outputs, (b) single antenna selection, (c) multiple antenna selection, and (d) linear processing of the antenna outputs. In each scenario, capacity is investigated as a function of the transmit power, the number of transmit/receive antennas and sign quantizers. In particular, it is shown that architecture (a) is sufficient to approach the optimal high signal-to-noise ratio (SNR)performance for a MIMO receiver in which the number of receive antennas is larger than the number of sign quantizers. Numerical evaluations of the average performance are presented for the case in which the channel gains are i.i.d. Gaussian distributed.

AB - The capacity of a discrete-time, multi-input multi-output (MIMO) channel with output quantization is investigated for different receiver architectures. A general framework for low-resolution quantization is proposed in which the antenna outputs are processed by analog combiners and sign quantizers are used for analog-to-digital conversion. The configuration of the analog combiners is chosen as a function of the channel realization so that the transmission rate can be maximized over the set of available configurations. To exemplify the proposed approach, four analog receiver architectures are considered: (a) sign quantization of the antenna outputs, (b) single antenna selection, (c) multiple antenna selection, and (d) linear processing of the antenna outputs. In each scenario, capacity is investigated as a function of the transmit power, the number of transmit/receive antennas and sign quantizers. In particular, it is shown that architecture (a) is sufficient to approach the optimal high signal-to-noise ratio (SNR)performance for a MIMO receiver in which the number of receive antennas is larger than the number of sign quantizers. Numerical evaluations of the average performance are presented for the case in which the channel gains are i.i.d. Gaussian distributed.

KW - Analog-to-digital conversion

KW - Channel output quantization

KW - MIMO channel

KW - One-bit quantization

UR - http://www.scopus.com/inward/record.url?scp=85046358609&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85046358609&partnerID=8YFLogxK

U2 - 10.1109/ITW.2017.8277991

DO - 10.1109/ITW.2017.8277991

M3 - Conference contribution

VL - 2018-January

SP - 599

EP - 603

BT - 2017 IEEE Information Theory Workshop, ITW 2017

PB - Institute of Electrical and Electronics Engineers Inc.

ER -