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Spectral efficiency optimization with channel state information of a massive MIMO System

The 5G network is expected to provide high data rate transmissions at very low latencies. To meet these high data rates the exploration of the under-utilized millimetre Wave (mm-Wave) frequency spectrum for hereafter broadband cellular communication networks is a focal point. Mm-Wave communication m...

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Main Author: Chingore, Paul Chakanetsa
Other Authors: Mwangama, Joyce
Format: Thesis
Language:English
Published: Department of Electrical Engineering 2023
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access_status_str Open Access
author Chingore, Paul Chakanetsa
author2 Mwangama, Joyce
author_browse Chingore, Paul Chakanetsa
Mwangama, Joyce
author_facet Mwangama, Joyce
Chingore, Paul Chakanetsa
author_sort Chingore, Paul Chakanetsa
collection Thesis
description The 5G network is expected to provide high data rate transmissions at very low latencies. To meet these high data rates the exploration of the under-utilized millimetre Wave (mm-Wave) frequency spectrum for hereafter broadband cellular communication networks is a focal point. Mm-Wave communication motivates the utilization of massive-MIMO. However, they are some limitations in the use of massive-MIMO since large –scale antenna arrays have high cost as well as the high-power consumption of huge Radio Frequency (RF) chains. This is a major drawback in the adoption of fully digital precoding in large-array systems. This research focuses on reducing the number of RF chains while using fixed large number of arrays for spatial multiplexing gains. A hybrid precoding architecture for mm Wave systems has been proposed for a system that has imperfect channel state information. Many wireless communication operations can be formulated as nonconvex non-smooth optimization problems. Often there is lack of effective algorithms for these problems especially in the event that the optimization variables are non-linear and coupled in some nonconvex constraints. To add on to that it is close to impossible to have perfect channel state information (CSI) in a wireless system. To optimize the spectral efficiency of imperfect CSI, an algorithm called penalty dual decomposition (PDD) is proposed for these problems. The PDD is a double-loop iterative algorithm that has a guaranteed convergence to Karush-Kuhn-Tucker (KKT) solution of the hybrid precoding problem under a mild assumption. The KKT solution supports the multi-stream transmission with few RF Chains. Simulation results reviews that the proposed PDD algorithm is capable of achieving better spectral efficiency than MAP and OMP even though they are few RF chains.
format Thesis
id oai:open.uct.ac.za:11427/37152
institution University of Cape Town (South Africa)
language eng
last_indexed 2026-06-10T12:39:31.448Z
license_str Not specified — see source repository
provenance_str_mv Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository
publishDate 2023
publishDateRange 2023
publishDateSort 2023
publisher Department of Electrical Engineering
publisherStr Department of Electrical Engineering
record_format dspace
source_str UCTD — University of Cape Town Open Access Repository
spelling oai:open.uct.ac.za:11427/37152 Spectral efficiency optimization with channel state information of a massive MIMO System Chingore, Paul Chakanetsa Mwangama, Joyce Electrical Engineering The 5G network is expected to provide high data rate transmissions at very low latencies. To meet these high data rates the exploration of the under-utilized millimetre Wave (mm-Wave) frequency spectrum for hereafter broadband cellular communication networks is a focal point. Mm-Wave communication motivates the utilization of massive-MIMO. However, they are some limitations in the use of massive-MIMO since large –scale antenna arrays have high cost as well as the high-power consumption of huge Radio Frequency (RF) chains. This is a major drawback in the adoption of fully digital precoding in large-array systems. This research focuses on reducing the number of RF chains while using fixed large number of arrays for spatial multiplexing gains. A hybrid precoding architecture for mm Wave systems has been proposed for a system that has imperfect channel state information. Many wireless communication operations can be formulated as nonconvex non-smooth optimization problems. Often there is lack of effective algorithms for these problems especially in the event that the optimization variables are non-linear and coupled in some nonconvex constraints. To add on to that it is close to impossible to have perfect channel state information (CSI) in a wireless system. To optimize the spectral efficiency of imperfect CSI, an algorithm called penalty dual decomposition (PDD) is proposed for these problems. The PDD is a double-loop iterative algorithm that has a guaranteed convergence to Karush-Kuhn-Tucker (KKT) solution of the hybrid precoding problem under a mild assumption. The KKT solution supports the multi-stream transmission with few RF Chains. Simulation results reviews that the proposed PDD algorithm is capable of achieving better spectral efficiency than MAP and OMP even though they are few RF chains. 2023-03-02T11:37:25Z 2023-03-02T11:37:25Z 2022 2023-02-20T12:24:39Z Master Thesis Masters MSc (Eng) http://hdl.handle.net/11427/37152 eng application/pdf Department of Electrical Engineering Faculty of Engineering and the Built Environment
spellingShingle Electrical Engineering
Chingore, Paul Chakanetsa
Spectral efficiency optimization with channel state information of a massive MIMO System
thesis_degree_str Master's
title Spectral efficiency optimization with channel state information of a massive MIMO System
title_full Spectral efficiency optimization with channel state information of a massive MIMO System
title_fullStr Spectral efficiency optimization with channel state information of a massive MIMO System
title_full_unstemmed Spectral efficiency optimization with channel state information of a massive MIMO System
title_short Spectral efficiency optimization with channel state information of a massive MIMO System
title_sort spectral efficiency optimization with channel state information of a massive mimo system
topic Electrical Engineering
url http://hdl.handle.net/11427/37152
work_keys_str_mv AT chingorepaulchakanetsa spectralefficiencyoptimizationwithchannelstateinformationofamassivemimosystem