Joint antenna selection and resource allocation for mm‐wave directional D2D communications using distributed deep reinforcement learning

Abstract In this paper, with the promising assumption of using adaptive directional microstrip antenna on user equipment, the problem of joint antenna selection, spectrum assignment, and transmit power allocation for mm‐wave device‐to‐device communications underlying cellular networks is tackled, wi...

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Main Authors: Pouya Akhoundzadeh, Ghasem Mirjalily
Format: Article
Language:English
Published: Wiley 2024-10-01
Series:Electronics Letters
Subjects:
Online Access:https://doi.org/10.1049/ell2.70066
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author Pouya Akhoundzadeh
Ghasem Mirjalily
author_facet Pouya Akhoundzadeh
Ghasem Mirjalily
author_sort Pouya Akhoundzadeh
collection DOAJ
description Abstract In this paper, with the promising assumption of using adaptive directional microstrip antenna on user equipment, the problem of joint antenna selection, spectrum assignment, and transmit power allocation for mm‐wave device‐to‐device communications underlying cellular networks is tackled, with the goal of enhancing system throughput and energy efficiency. To address the complexity of this problem, a method based on multi‐agent distributed deep reinforcement learning in which an autonomous intelligent agent is deployed for each user equipment is proposed. The performance evaluation demonstrates its superiority over existing strategies, resulting in improved system performance, reduced outage probability, and enhanced energy efficiency.
format Article
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institution OA Journals
issn 0013-5194
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publishDate 2024-10-01
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series Electronics Letters
spelling doaj-art-e359109cd9bc4d2d94e28e5f075e14422025-08-20T01:54:16ZengWileyElectronics Letters0013-51941350-911X2024-10-016020n/an/a10.1049/ell2.70066Joint antenna selection and resource allocation for mm‐wave directional D2D communications using distributed deep reinforcement learningPouya Akhoundzadeh0Ghasem Mirjalily1Department of Electrical Engineering Yazd University Yazd IranDepartment of Electrical Engineering Yazd University Yazd IranAbstract In this paper, with the promising assumption of using adaptive directional microstrip antenna on user equipment, the problem of joint antenna selection, spectrum assignment, and transmit power allocation for mm‐wave device‐to‐device communications underlying cellular networks is tackled, with the goal of enhancing system throughput and energy efficiency. To address the complexity of this problem, a method based on multi‐agent distributed deep reinforcement learning in which an autonomous intelligent agent is deployed for each user equipment is proposed. The performance evaluation demonstrates its superiority over existing strategies, resulting in improved system performance, reduced outage probability, and enhanced energy efficiency.https://doi.org/10.1049/ell2.700665G mobile communicationlearning (artificial intelligence)millimetre wave antennas
spellingShingle Pouya Akhoundzadeh
Ghasem Mirjalily
Joint antenna selection and resource allocation for mm‐wave directional D2D communications using distributed deep reinforcement learning
Electronics Letters
5G mobile communication
learning (artificial intelligence)
millimetre wave antennas
title Joint antenna selection and resource allocation for mm‐wave directional D2D communications using distributed deep reinforcement learning
title_full Joint antenna selection and resource allocation for mm‐wave directional D2D communications using distributed deep reinforcement learning
title_fullStr Joint antenna selection and resource allocation for mm‐wave directional D2D communications using distributed deep reinforcement learning
title_full_unstemmed Joint antenna selection and resource allocation for mm‐wave directional D2D communications using distributed deep reinforcement learning
title_short Joint antenna selection and resource allocation for mm‐wave directional D2D communications using distributed deep reinforcement learning
title_sort joint antenna selection and resource allocation for mm wave directional d2d communications using distributed deep reinforcement learning
topic 5G mobile communication
learning (artificial intelligence)
millimetre wave antennas
url https://doi.org/10.1049/ell2.70066
work_keys_str_mv AT pouyaakhoundzadeh jointantennaselectionandresourceallocationformmwavedirectionald2dcommunicationsusingdistributeddeepreinforcementlearning
AT ghasemmirjalily jointantennaselectionandresourceallocationformmwavedirectionald2dcommunicationsusingdistributeddeepreinforcementlearning