Antenna Selection for Improving Energy Efficiency in XL-MIMO Systems

José Carlos Marinello, Taufik Abrão, Abolfazl Amiri, Elisabeth De Carvalho, Petar Popovski

Research output: Contribution to journalJournal articleResearchpeer-review

13 Citations (Scopus)
2 Downloads (Pure)

Abstract

We consider the recently proposed extra-large scale massive multiple-input multiple-output (XL-MIMO) systems, with some hundreds of antennas serving a smaller number of users. Since the array length is of the same order as the distance to the users, the long-term fading coefficients of a given user vary with the different antennas at the base station (BS). Thus, the signal transmitted by some antennas might reach the user with much more power than that transmitted by some others. From a green perspective, it is not effective to simultaneously activate hundreds or even thousands of antennas, since the power-hungry radio frequency (RF) chains of the active antennas increase significantly the total energy consumption. Besides, a larger number of selected antennas increases the power required by linear processing, such as precoding matrix computation, and short-term channel estimation. In this paper, we propose four antenna selection (AS) approaches to be deployed in XL-MIMO systems aiming at maximizing the total energy efficiency (EE). Besides, employing some simplifying assumptions, we derive a closed-form analytical expression for the EE of the XL-MIMO system, and propose a straightforward iterative method to determine the optimal number of selected antennas able to maximize it. The proposed AS schemes are based solely on long-term fading parameters, thus, the selected antennas set remains valid for a relatively large time/frequency intervals. Comparing the results, we find that the genetic-algorithm based AS scheme usually achieves the best EE performance, although our proposed highest normalized received power AS scheme also achieves very promising EE performance in a simple and straightforward way.
Original languageEnglish
Article number9187980
JournalI E E E Transactions on Vehicular Technology
Volume69
Issue number11
Pages (from-to)13305-13318
Number of pages14
ISSN0018-9545
DOIs
Publication statusPublished - Nov 2020

Keywords

  • Extra large-scale MIMO
  • antenna selection
  • energy efficiency
  • near-field
  • non-stationary
  • spectral efficiency
  • visibility region (VR)

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