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Resource Management and Backhaul Routing in Millimeter-Wave IAB Networks Using Deep Reinforcement Learning
Thesis (PhD (Electronic Engineering))--University of Pretoria, 2023..
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2023
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| _version_ | 1867613721300303872 |
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| access_status_str | Open Access |
| author2 | Maharaj, Sunil |
| author_browse | Maharaj, Sunil |
| author_facet | Maharaj, Sunil |
| collection | Thesis |
| dc_rights_str_mv | © 2022 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
| description | Thesis (PhD (Electronic Engineering))--University of Pretoria, 2023.. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/89854 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:40:38.899Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/89854 Resource Management and Backhaul Routing in Millimeter-Wave IAB Networks Using Deep Reinforcement Learning Maharaj, Sunil malcolm.sande@gmail.com Sande, Malcolm Makomborero UCTD Wireless Communications Machine learning Congestion control Deep reinforcement learning Integrated access and backhaul Thesis (PhD (Electronic Engineering))--University of Pretoria, 2023.. The increased densification of wireless networks has led to the development of integrated access and backhaul (IAB) networks. In this thesis, deep reinforcement learning was applied to solve resource management and backhaul routing problems in millimeter-wave IAB networks. In the research work, a resource management solution that aims to avoid congestion for access users in an IAB network was proposed and implemented. The proposed solution applies deep reinforcement learning to learn an optimized policy that aims to achieve effective resource allocation whilst minimizing congestion and satisfying the user requirements. In addition, a deep reinforcement learning-based backhaul adaptation strategy that leverages a recursive discrete choice model was implemented in simulation. Simulation results where the proposed algorithms were compared with two baseline methods showed that the proposed scheme provides better throughput and delay performance. Sentech Chair in Broadband Wireless Multimedia Communications. Electrical, Electronic and Computer Engineering PhD (Electronic Engineering) Unrestricted 2023-02-27T10:58:42Z 2023-02-27T10:58:42Z 2023-05-12 2023 Thesis * A2023 https://repository.up.ac.za/handle/2263/89854 https://doi.org/10.25403/UPresearchdata.22182295 en © 2022 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf University of Pretoria |
| spellingShingle | UCTD Wireless Communications Machine learning Congestion control Deep reinforcement learning Integrated access and backhaul Resource Management and Backhaul Routing in Millimeter-Wave IAB Networks Using Deep Reinforcement Learning |
| title | Resource Management and Backhaul Routing in Millimeter-Wave IAB Networks Using Deep Reinforcement Learning |
| title_full | Resource Management and Backhaul Routing in Millimeter-Wave IAB Networks Using Deep Reinforcement Learning |
| title_fullStr | Resource Management and Backhaul Routing in Millimeter-Wave IAB Networks Using Deep Reinforcement Learning |
| title_full_unstemmed | Resource Management and Backhaul Routing in Millimeter-Wave IAB Networks Using Deep Reinforcement Learning |
| title_short | Resource Management and Backhaul Routing in Millimeter-Wave IAB Networks Using Deep Reinforcement Learning |
| title_sort | resource management and backhaul routing in millimeter wave iab networks using deep reinforcement learning |
| topic | UCTD Wireless Communications Machine learning Congestion control Deep reinforcement learning Integrated access and backhaul |
| url | https://repository.up.ac.za/handle/2263/89854 https://doi.org/10.25403/UPresearchdata.22182295 |