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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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/ |
work_keys_str_mv |
AT malcolmmsande fastconvergingrobustbeamformingformassivemimoinheterogeneousnetworks AT soumayahamouda fastconvergingrobustbeamformingformassivemimoinheterogeneousnetworks AT btmaharaj fastconvergingrobustbeamformingformassivemimoinheterogeneousnetworks |
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1724194281311174656 |