Beamforming and power allocation for energy-efficient massive MIMO

Quang Duong

doi:10.1109/ICDSP.2017.8096127

Beamforming and power allocation for energy-efficient massive MIMO

Quang Duong

School of Electronics, Electrical Engineering and Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

16 Citations (Scopus)

Abstract

Massive multiple input multiple output (MIMO) has emerged as a promising technology, which utilizes a large number of antennas at base stations (BSs) to significantly improve the spectral efficiency in terms of bits/s/Hz while reducing the radiated signal power. A critical issue with massive MIMO is the costly circuit power consumption, which is proportional to the number of antennas. This paper develops low-complexity power allocation techniques to apply beamforming and to maximize the energy efficiency of massive MIMO while meeting users' quality-of-service requirements. Algorithms of low computational complexity with rapid convergence are proposed to solve for the optimal beamformer in this sense. Numerical examples are provided to show the merit of the proposed computational approach.

Original language	English
Title of host publication	IEEE Digital Signal Processing Conference (DSP'17): Proceedings
Place of Publication	London, UK
Publisher	Institute of Electrical and Electronics Engineers Inc.
Number of pages	5
ISBN (Print)	978-1-5386-1895-0
DOIs	https://doi.org/10.1109/ICDSP.2017.8096127
Publication status	Published - 07 Nov 2017

Publication series

Name	International Conference on Digital Signal Processing (DSP): Proceedings
ISSN (Electronic)	2165-3577

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

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10.1109/ICDSP.2017.8096127

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abstract = "Massive multiple input multiple output (MIMO) has emerged as a promising technology, which utilizes a large number of antennas at base stations (BSs) to significantly improve the spectral efficiency in terms of bits/s/Hz while reducing the radiated signal power. A critical issue with massive MIMO is the costly circuit power consumption, which is proportional to the number of antennas. This paper develops low-complexity power allocation techniques to apply beamforming and to maximize the energy efficiency of massive MIMO while meeting users' quality-of-service requirements. Algorithms of low computational complexity with rapid convergence are proposed to solve for the optimal beamformer in this sense. Numerical examples are provided to show the merit of the proposed computational approach.",

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doi = "10.1109/ICDSP.2017.8096127",

language = "English",

isbn = "978-1-5386-1895-0",

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Beamforming and power allocation for energy-efficient massive MIMO. / Duong, Quang.
IEEE Digital Signal Processing Conference (DSP'17): Proceedings. London, UK: Institute of Electrical and Electronics Engineers Inc., 2017. (International Conference on Digital Signal Processing (DSP): Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N2 - Massive multiple input multiple output (MIMO) has emerged as a promising technology, which utilizes a large number of antennas at base stations (BSs) to significantly improve the spectral efficiency in terms of bits/s/Hz while reducing the radiated signal power. A critical issue with massive MIMO is the costly circuit power consumption, which is proportional to the number of antennas. This paper develops low-complexity power allocation techniques to apply beamforming and to maximize the energy efficiency of massive MIMO while meeting users' quality-of-service requirements. Algorithms of low computational complexity with rapid convergence are proposed to solve for the optimal beamformer in this sense. Numerical examples are provided to show the merit of the proposed computational approach.

AB - Massive multiple input multiple output (MIMO) has emerged as a promising technology, which utilizes a large number of antennas at base stations (BSs) to significantly improve the spectral efficiency in terms of bits/s/Hz while reducing the radiated signal power. A critical issue with massive MIMO is the costly circuit power consumption, which is proportional to the number of antennas. This paper develops low-complexity power allocation techniques to apply beamforming and to maximize the energy efficiency of massive MIMO while meeting users' quality-of-service requirements. Algorithms of low computational complexity with rapid convergence are proposed to solve for the optimal beamformer in this sense. Numerical examples are provided to show the merit of the proposed computational approach.

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DO - 10.1109/ICDSP.2017.8096127

M3 - Conference contribution

SN - 978-1-5386-1895-0

T3 - International Conference on Digital Signal Processing (DSP): Proceedings

BT - IEEE Digital Signal Processing Conference (DSP'17): Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

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ER -

Beamforming and power allocation for energy-efficient massive MIMO

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