Law of large numbers analysis of antenna selection aided downlink beamforming in massive MISO under RF chains constraint

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearchpeer-review

Abstract

Massive MIMO has potential to offer massive throughputs by mounting a large number of antennas at the base station. One of the major limitations of massive MIMO is the cost of a huge number of RF chains. Antenna Selection is a promising signal processing technique which reduces the number of required RF chains while keeping the system's performance at a certain minimum level. In this paper, we investigate the capacity performance of an antenna selection scheme employed in a massive MISO system. The main contribution of this paper is a theorem which provides a concise formula for the limiting normalized channel power gain in the considered scheme. The deterministic equivalent of the normalized channel power gain is valid in the regime when the number of RF chains, Nc, and the number of base station antennas, NT, tend to infinity while maintaining fixed ratio β = Nc/NT. Numerical experiments suggest that the deterministic equivalents are accurate even for relatively small Nc, NT.

LanguageEnglish
Title of host publication2016 Australian Communications Theory Workshop, AusCTW 2016
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages163-168
Number of pages6
ISBN (Electronic)9781509001330
DOIs
Publication statusPublished - 14 Mar 2016
EventAustralian Communications Theory Workshop, AusCTW 2016 - Melbourne, Australia
Duration: 20 Jan 201623 Jan 2016

Other

OtherAustralian Communications Theory Workshop, AusCTW 2016
CountryAustralia
CityMelbourne
Period20/01/1623/01/16

Fingerprint

Beamforming
Antennas
MIMO systems
Base stations
Mountings
Signal processing
Throughput
Costs
Experiments

Keywords

  • Antenna Selection
  • Asymptotic Limit
  • Massive MIMO

Cite this

Hanly, S. V., Collings, I. B., Shaikh, Z. A., & Whiting, P. (2016). Law of large numbers analysis of antenna selection aided downlink beamforming in massive MISO under RF chains constraint. In 2016 Australian Communications Theory Workshop, AusCTW 2016 (pp. 163-168). [7433668] Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/AusCTW.2016.7433668
Hanly, S. V. ; Collings, I. B. ; Shaikh, Z. A. ; Whiting, P. / Law of large numbers analysis of antenna selection aided downlink beamforming in massive MISO under RF chains constraint. 2016 Australian Communications Theory Workshop, AusCTW 2016. Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2016. pp. 163-168
@inproceedings{ed4ac801986c4da9ad6a18884cf0517a,
title = "Law of large numbers analysis of antenna selection aided downlink beamforming in massive MISO under RF chains constraint",
abstract = "Massive MIMO has potential to offer massive throughputs by mounting a large number of antennas at the base station. One of the major limitations of massive MIMO is the cost of a huge number of RF chains. Antenna Selection is a promising signal processing technique which reduces the number of required RF chains while keeping the system's performance at a certain minimum level. In this paper, we investigate the capacity performance of an antenna selection scheme employed in a massive MISO system. The main contribution of this paper is a theorem which provides a concise formula for the limiting normalized channel power gain in the considered scheme. The deterministic equivalent of the normalized channel power gain is valid in the regime when the number of RF chains, Nc, and the number of base station antennas, NT, tend to infinity while maintaining fixed ratio β = Nc/NT. Numerical experiments suggest that the deterministic equivalents are accurate even for relatively small Nc, NT.",
keywords = "Antenna Selection, Asymptotic Limit, Massive MIMO",
author = "Hanly, {S. V.} and Collings, {I. B.} and Shaikh, {Z. A.} and P. Whiting",
year = "2016",
month = "3",
day = "14",
doi = "10.1109/AusCTW.2016.7433668",
language = "English",
pages = "163--168",
booktitle = "2016 Australian Communications Theory Workshop, AusCTW 2016",
publisher = "Institute of Electrical and Electronics Engineers (IEEE)",
address = "United States",

}

Hanly, SV, Collings, IB, Shaikh, ZA & Whiting, P 2016, Law of large numbers analysis of antenna selection aided downlink beamforming in massive MISO under RF chains constraint. in 2016 Australian Communications Theory Workshop, AusCTW 2016., 7433668, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, NJ, pp. 163-168, Australian Communications Theory Workshop, AusCTW 2016, Melbourne, Australia, 20/01/16. https://doi.org/10.1109/AusCTW.2016.7433668

Law of large numbers analysis of antenna selection aided downlink beamforming in massive MISO under RF chains constraint. / Hanly, S. V.; Collings, I. B.; Shaikh, Z. A.; Whiting, P.

2016 Australian Communications Theory Workshop, AusCTW 2016. Piscataway, NJ : Institute of Electrical and Electronics Engineers (IEEE), 2016. p. 163-168 7433668.

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionResearchpeer-review

TY - GEN

T1 - Law of large numbers analysis of antenna selection aided downlink beamforming in massive MISO under RF chains constraint

AU - Hanly, S. V.

AU - Collings, I. B.

AU - Shaikh, Z. A.

AU - Whiting, P.

PY - 2016/3/14

Y1 - 2016/3/14

N2 - Massive MIMO has potential to offer massive throughputs by mounting a large number of antennas at the base station. One of the major limitations of massive MIMO is the cost of a huge number of RF chains. Antenna Selection is a promising signal processing technique which reduces the number of required RF chains while keeping the system's performance at a certain minimum level. In this paper, we investigate the capacity performance of an antenna selection scheme employed in a massive MISO system. The main contribution of this paper is a theorem which provides a concise formula for the limiting normalized channel power gain in the considered scheme. The deterministic equivalent of the normalized channel power gain is valid in the regime when the number of RF chains, Nc, and the number of base station antennas, NT, tend to infinity while maintaining fixed ratio β = Nc/NT. Numerical experiments suggest that the deterministic equivalents are accurate even for relatively small Nc, NT.

AB - Massive MIMO has potential to offer massive throughputs by mounting a large number of antennas at the base station. One of the major limitations of massive MIMO is the cost of a huge number of RF chains. Antenna Selection is a promising signal processing technique which reduces the number of required RF chains while keeping the system's performance at a certain minimum level. In this paper, we investigate the capacity performance of an antenna selection scheme employed in a massive MISO system. The main contribution of this paper is a theorem which provides a concise formula for the limiting normalized channel power gain in the considered scheme. The deterministic equivalent of the normalized channel power gain is valid in the regime when the number of RF chains, Nc, and the number of base station antennas, NT, tend to infinity while maintaining fixed ratio β = Nc/NT. Numerical experiments suggest that the deterministic equivalents are accurate even for relatively small Nc, NT.

KW - Antenna Selection

KW - Asymptotic Limit

KW - Massive MIMO

UR - http://www.scopus.com/inward/record.url?scp=84965062483&partnerID=8YFLogxK

U2 - 10.1109/AusCTW.2016.7433668

DO - 10.1109/AusCTW.2016.7433668

M3 - Conference proceeding contribution

SP - 163

EP - 168

BT - 2016 Australian Communications Theory Workshop, AusCTW 2016

PB - Institute of Electrical and Electronics Engineers (IEEE)

CY - Piscataway, NJ

ER -

Hanly SV, Collings IB, Shaikh ZA, Whiting P. Law of large numbers analysis of antenna selection aided downlink beamforming in massive MISO under RF chains constraint. In 2016 Australian Communications Theory Workshop, AusCTW 2016. Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE). 2016. p. 163-168. 7433668 https://doi.org/10.1109/AusCTW.2016.7433668