Extremely Large Aperture Massive MIMO: Low Complexity Receiver Architectures

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

Abstract

This paper focuses on new communication paradigms arising in massive multiple-input-multiple-output systems where the antenna array at the base station is of extremely large dimension (xMaMIMO). Due to the extreme dimension of the array, xMaMIMO is characterized by spatial non-stationary field properties along the array; this calls for a multi-antenna transceiver design that is adapted to the array dimension but also its non-stationary properties. We address implementation aspects of xMaMIMO, with computational efficiency as our primary objective. To reduce the computational burden of centralized schemes, we distribute the processing into smaller, disjoint subarrays. Then, we consider several low-complexity data detection algorithms as candidates for uplink communication in crowded xMaMIMO systems. Drawing inspiration from coded random access, one of the main contributions of the paper is the design of low complexity scheme that exploits the non-stationary nature of xMaMIMO systems and where the data processing is decentralized. We evaluate the bit-error-rate performance of the transceivers in crowded xMaMIMO scenarios. The results confirm their practical potential.
Original languageEnglish
Title of host publication2018 IEEE Globecom Workshops (GC Wkshps)
Number of pages6
PublisherIEEE
Publication date21 Feb 2019
ISBN (Print)978-1-5386-4921-3
ISBN (Electronic)978-1-5386-4920-6
DOIs
Publication statusPublished - 21 Feb 2019
Event2018 IEEE Globecom Workshops (GC Wkshps) - Abu Dhabi, United Arab Emirates
Duration: 9 Dec 201813 Dec 2018

Conference

Conference2018 IEEE Globecom Workshops (GC Wkshps)
CountryUnited Arab Emirates
CityAbu Dhabi
Period09/12/201813/12/2018

Fingerprint

MIMO systems
Transceivers
Communication
Computational efficiency
Antenna arrays
Base stations
Bit error rate
Antennas
Processing

Cite this

@inproceedings{6a3b84c5521c40309b5d1e6692e636af,
title = "Extremely Large Aperture Massive MIMO: Low Complexity Receiver Architectures",
abstract = "This paper focuses on new communication paradigms arising in massive multiple-input-multiple-output systems where the antenna array at the base station is of extremely large dimension (xMaMIMO). Due to the extreme dimension of the array, xMaMIMO is characterized by spatial non-stationary field properties along the array; this calls for a multi-antenna transceiver design that is adapted to the array dimension but also its non-stationary properties. We address implementation aspects of xMaMIMO, with computational efficiency as our primary objective. To reduce the computational burden of centralized schemes, we distribute the processing into smaller, disjoint subarrays. Then, we consider several low-complexity data detection algorithms as candidates for uplink communication in crowded xMaMIMO systems. Drawing inspiration from coded random access, one of the main contributions of the paper is the design of low complexity scheme that exploits the non-stationary nature of xMaMIMO systems and where the data processing is decentralized. We evaluate the bit-error-rate performance of the transceivers in crowded xMaMIMO scenarios. The results confirm their practical potential.",
author = "Abolfazl Amiri and Marko Angjelichinoski and Carvalho, {Elisabeth De} and {Heath Jr}, {Robert W}",
year = "2019",
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doi = "10.1109/GLOCOMW.2018.8644126",
language = "English",
isbn = "978-1-5386-4921-3",
booktitle = "2018 IEEE Globecom Workshops (GC Wkshps)",
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Amiri, A, Angjelichinoski, M, Carvalho, ED & Heath Jr, RW 2019, Extremely Large Aperture Massive MIMO: Low Complexity Receiver Architectures. in 2018 IEEE Globecom Workshops (GC Wkshps). IEEE, 2018 IEEE Globecom Workshops (GC Wkshps), Abu Dhabi, United Arab Emirates, 09/12/2018. https://doi.org/10.1109/GLOCOMW.2018.8644126

Extremely Large Aperture Massive MIMO: Low Complexity Receiver Architectures. / Amiri, Abolfazl; Angjelichinoski, Marko; Carvalho, Elisabeth De; Heath Jr, Robert W .

2018 IEEE Globecom Workshops (GC Wkshps). IEEE, 2019.

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

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N2 - This paper focuses on new communication paradigms arising in massive multiple-input-multiple-output systems where the antenna array at the base station is of extremely large dimension (xMaMIMO). Due to the extreme dimension of the array, xMaMIMO is characterized by spatial non-stationary field properties along the array; this calls for a multi-antenna transceiver design that is adapted to the array dimension but also its non-stationary properties. We address implementation aspects of xMaMIMO, with computational efficiency as our primary objective. To reduce the computational burden of centralized schemes, we distribute the processing into smaller, disjoint subarrays. Then, we consider several low-complexity data detection algorithms as candidates for uplink communication in crowded xMaMIMO systems. Drawing inspiration from coded random access, one of the main contributions of the paper is the design of low complexity scheme that exploits the non-stationary nature of xMaMIMO systems and where the data processing is decentralized. We evaluate the bit-error-rate performance of the transceivers in crowded xMaMIMO scenarios. The results confirm their practical potential.

AB - This paper focuses on new communication paradigms arising in massive multiple-input-multiple-output systems where the antenna array at the base station is of extremely large dimension (xMaMIMO). Due to the extreme dimension of the array, xMaMIMO is characterized by spatial non-stationary field properties along the array; this calls for a multi-antenna transceiver design that is adapted to the array dimension but also its non-stationary properties. We address implementation aspects of xMaMIMO, with computational efficiency as our primary objective. To reduce the computational burden of centralized schemes, we distribute the processing into smaller, disjoint subarrays. Then, we consider several low-complexity data detection algorithms as candidates for uplink communication in crowded xMaMIMO systems. Drawing inspiration from coded random access, one of the main contributions of the paper is the design of low complexity scheme that exploits the non-stationary nature of xMaMIMO systems and where the data processing is decentralized. We evaluate the bit-error-rate performance of the transceivers in crowded xMaMIMO scenarios. The results confirm their practical potential.

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