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

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4 Citations (Scopus)

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.

Original 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

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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