Fast Converging Robust Beamforming for Massive MIMO in Heterogeneous Networks

The use of massive multiple-input multiple-output (MIMO) base stations in heterogeneous networks (HetNets) offers an increase in throughput without increasing the bandwidth, but with reduced power consumption. In this paper, we investigate the optimization problem of signal-to-interference-plusnoise...

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Main Authors: Malcolm M. Sande, Soumaya Hamouda, B. T. Maharaj
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8345283/
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spelling doaj-af6aca0a2523400b97144fdfb25c6b012021-03-29T20:44:23ZengIEEEIEEE Access2169-35362018-01-016239182392810.1109/ACCESS.2018.28295348345283Fast Converging Robust Beamforming for Massive MIMO in Heterogeneous NetworksMalcolm M. Sande0https://orcid.org/0000-0002-6636-2050Soumaya Hamouda1B. T. Maharaj2Department of Electrical, Electronic and Computer Engineering, University of Pretoria, Pretoria, South AfricaMediatron Laboratory, Sup’Com, University of Carthage, Carthage, TunisiaFaculty of Engineering, Built Environment and IT, University of Pretoria, Pretoria, South AfricaThe use of massive multiple-input multiple-output (MIMO) base stations in heterogeneous networks (HetNets) offers an increase in throughput without increasing the bandwidth, but with reduced power consumption. In this paper, we investigate the optimization problem of signal-to-interference-plusnoise ratio balancing for the case of imperfect channel state information at the transmitter. We present a fast converging robust beamforming solution for macrocell users in a typical HetNet scenario with massive MIMO at the base station. The proposed method applies the matrix stuffing technique and the alternative direction method of multipliers to give an efficient solution. Simulation results of a single-cell heterogeneous network show that the proposed solution yields performance with modest accuracy, while converging in an efficient manner, compared with optimal solutions achieved by the state-of-the-art modeling languages and interior-point solvers. This is particularly for cases when the number of antennas at the base station increases to large values. This makes the solution method attractive for practical implementation in heterogeneous networks with large-scale antenna arrays at the macrocell base station.https://ieeexplore.ieee.org/document/8345283/Massive MIMOHetNetmacrocellbeamformingmatrix stuffingADMM algorithm
collection DOAJ
language English
format Article
sources DOAJ
author Malcolm M. Sande
Soumaya Hamouda
B. T. Maharaj
spellingShingle Malcolm M. Sande
Soumaya Hamouda
B. T. Maharaj
Fast Converging Robust Beamforming for Massive MIMO in Heterogeneous Networks
IEEE Access
Massive MIMO
HetNet
macrocell
beamforming
matrix stuffing
ADMM algorithm
author_facet Malcolm M. Sande
Soumaya Hamouda
B. T. Maharaj
author_sort Malcolm M. Sande
title Fast Converging Robust Beamforming for Massive MIMO in Heterogeneous Networks
title_short Fast Converging Robust Beamforming for Massive MIMO in Heterogeneous Networks
title_full Fast Converging Robust Beamforming for Massive MIMO in Heterogeneous Networks
title_fullStr Fast Converging Robust Beamforming for Massive MIMO in Heterogeneous Networks
title_full_unstemmed Fast Converging Robust Beamforming for Massive MIMO in Heterogeneous Networks
title_sort fast converging robust beamforming for massive mimo in heterogeneous networks
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2018-01-01
description The use of massive multiple-input multiple-output (MIMO) base stations in heterogeneous networks (HetNets) offers an increase in throughput without increasing the bandwidth, but with reduced power consumption. In this paper, we investigate the optimization problem of signal-to-interference-plusnoise ratio balancing for the case of imperfect channel state information at the transmitter. We present a fast converging robust beamforming solution for macrocell users in a typical HetNet scenario with massive MIMO at the base station. The proposed method applies the matrix stuffing technique and the alternative direction method of multipliers to give an efficient solution. Simulation results of a single-cell heterogeneous network show that the proposed solution yields performance with modest accuracy, while converging in an efficient manner, compared with optimal solutions achieved by the state-of-the-art modeling languages and interior-point solvers. This is particularly for cases when the number of antennas at the base station increases to large values. This makes the solution method attractive for practical implementation in heterogeneous networks with large-scale antenna arrays at the macrocell base station.
topic Massive MIMO
HetNet
macrocell
beamforming
matrix stuffing
ADMM algorithm
url https://ieeexplore.ieee.org/document/8345283/
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AT soumayahamouda fastconvergingrobustbeamformingformassivemimoinheterogeneousnetworks
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