Refiner GAN Algorithmically Enabled Deep-RL for Guaranteed Traffic Packets in Real-Time URLLC B5G Communication Systems Article Swipe
Adeeb Salh
,
Lukman Audah
,
Kwang Soon Kim
,
Saeed Hamood Alsamhi
,
Mohammed A. Alhartomi
,
Qazwan Abdullah
,
Faris A. Almalki
,
Haneen Algethami
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1109/access.2022.3170447
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1109/access.2022.3170447
Ultra-reliable and Low-latency Communications (URLLC) is expected to be one of the most critical characteristics Beyond fifth-Generation (B5G) cellular networks with stringent low latency and high-reliability requirements. The Deep Reinforcement Learning (deep-RL) framework has been applied to predict the optimization of a Resource Block (RB) and minimize Power Allocation (PA) to guarantee a high End-to-End (E2E) reliability and low E2E latency under rate constraints. This paper proposes a novel Policy Gradient-based Actor-Critic Learning (PGACL) algorithm to optimize the policy gradient for optimal rate allocation to solve the RB, minimize power, and guarantee a solution for URLLC scheduling. The purpose of a PGACL algorithm is to provide a good policy with a closer convergence rate and a low computational cost depending on the reduced action space for every user. URLLC systems need to operate in highly reliable systems and account for extreme network conditions. Therefore, we proposed the refiner Generative Adversarial Networks (GANs) that apply enough extreme events for the deep-RL agent to generate synthetic data with high reliability similar to real data based on the regulated number of extreme events in the dataset. This refiner GAN method enables a deep-RL approach to generate large amounts of data practically used in real-time operations. Simulation results showed that the proposed deep-RL for refiner-GAN can omit the transient training time and develop deep learning based on a controlled set of unlabeled real traffic at a relatively short time. Furthermore, the refiner GAN demonstrated 99.9999% reliability and E2E latency of less than 1.4ms.
Related Topics
Concepts
Computer science
Reinforcement learning
Latency (audio)
Network packet
Deep learning
Scheduling (production processes)
Reliability (semiconductor)
Optimization problem
Distributed computing
Real-time computing
Mathematical optimization
Artificial intelligence
Algorithm
Power (physics)
Computer network
Mathematics
Quantum mechanics
Physics
Telecommunications
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/access.2022.3170447
- https://ieeexplore.ieee.org/ielx7/6287639/9668973/09762938.pdf
- OA Status
- gold
- Cited By
- 27
- References
- 41
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4225463090
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4225463090Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1109/access.2022.3170447Digital Object Identifier
- Title
-
Refiner GAN Algorithmically Enabled Deep-RL for Guaranteed Traffic Packets in Real-Time URLLC B5G Communication SystemsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-01-01Full publication date if available
- Authors
-
Adeeb Salh, Lukman Audah, Kwang Soon Kim, Saeed Hamood Alsamhi, Mohammed A. Alhartomi, Qazwan Abdullah, Faris A. Almalki, Haneen AlgethamiList of authors in order
- Landing page
-
https://doi.org/10.1109/access.2022.3170447Publisher landing page
- PDF URL
-
https://ieeexplore.ieee.org/ielx7/6287639/9668973/09762938.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://ieeexplore.ieee.org/ielx7/6287639/9668973/09762938.pdfDirect OA link when available
- Concepts
-
Computer science, Reinforcement learning, Latency (audio), Network packet, Deep learning, Scheduling (production processes), Reliability (semiconductor), Optimization problem, Distributed computing, Real-time computing, Mathematical optimization, Artificial intelligence, Algorithm, Power (physics), Computer network, Mathematics, Quantum mechanics, Physics, TelecommunicationsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
27Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 4, 2024: 5, 2023: 8, 2022: 10Per-year citation counts (last 5 years)
- References (count)
-
41Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4225463090 |
|---|---|
| doi | https://doi.org/10.1109/access.2022.3170447 |
| ids.doi | https://doi.org/10.1109/access.2022.3170447 |
| ids.openalex | https://openalex.org/W4225463090 |
| fwci | 2.90646145 |
| type | article |
| title | Refiner GAN Algorithmically Enabled Deep-RL for Guaranteed Traffic Packets in Real-Time URLLC B5G Communication Systems |
| biblio.issue | |
| biblio.volume | 10 |
| biblio.last_page | 50676 |
| biblio.first_page | 50662 |
| topics[0].id | https://openalex.org/T10964 |
| topics[0].field.id | https://openalex.org/fields/22 |
| topics[0].field.display_name | Engineering |
| topics[0].score | 0.9995999932289124 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2208 |
| topics[0].subfield.display_name | Electrical and Electronic Engineering |
| topics[0].display_name | Wireless Communication Security Techniques |
| topics[1].id | https://openalex.org/T12131 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.9986000061035156 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1702 |
| topics[1].subfield.display_name | Artificial Intelligence |
| topics[1].display_name | Wireless Signal Modulation Classification |
| topics[2].id | https://openalex.org/T10148 |
| topics[2].field.id | https://openalex.org/fields/22 |
| topics[2].field.display_name | Engineering |
| topics[2].score | 0.9986000061035156 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2208 |
| topics[2].subfield.display_name | Electrical and Electronic Engineering |
| topics[2].display_name | Advanced MIMO Systems Optimization |
| is_xpac | False |
| apc_list.value | 1850 |
| apc_list.currency | USD |
| apc_list.value_usd | 1850 |
| apc_paid.value | 1850 |
| apc_paid.currency | USD |
| apc_paid.value_usd | 1850 |
| concepts[0].id | https://openalex.org/C41008148 |
| concepts[0].level | 0 |
| concepts[0].score | 0.82724529504776 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[0].display_name | Computer science |
| concepts[1].id | https://openalex.org/C97541855 |
| concepts[1].level | 2 |
| concepts[1].score | 0.7160155773162842 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q830687 |
| concepts[1].display_name | Reinforcement learning |
| concepts[2].id | https://openalex.org/C82876162 |
| concepts[2].level | 2 |
| concepts[2].score | 0.6306509375572205 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q17096504 |
| concepts[2].display_name | Latency (audio) |
| concepts[3].id | https://openalex.org/C158379750 |
| concepts[3].level | 2 |
| concepts[3].score | 0.5822203159332275 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q214111 |
| concepts[3].display_name | Network packet |
| concepts[4].id | https://openalex.org/C108583219 |
| concepts[4].level | 2 |
| concepts[4].score | 0.4729616045951843 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q197536 |
| concepts[4].display_name | Deep learning |
| concepts[5].id | https://openalex.org/C206729178 |
| concepts[5].level | 2 |
| concepts[5].score | 0.4657132625579834 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q2271896 |
| concepts[5].display_name | Scheduling (production processes) |
| concepts[6].id | https://openalex.org/C43214815 |
| concepts[6].level | 3 |
| concepts[6].score | 0.4618344306945801 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q7310987 |
| concepts[6].display_name | Reliability (semiconductor) |
| concepts[7].id | https://openalex.org/C137836250 |
| concepts[7].level | 2 |
| concepts[7].score | 0.4137353003025055 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q984063 |
| concepts[7].display_name | Optimization problem |
| concepts[8].id | https://openalex.org/C120314980 |
| concepts[8].level | 1 |
| concepts[8].score | 0.3784952163696289 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q180634 |
| concepts[8].display_name | Distributed computing |
| concepts[9].id | https://openalex.org/C79403827 |
| concepts[9].level | 1 |
| concepts[9].score | 0.3743666410446167 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q3988 |
| concepts[9].display_name | Real-time computing |
| concepts[10].id | https://openalex.org/C126255220 |
| concepts[10].level | 1 |
| concepts[10].score | 0.3050065338611603 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q141495 |
| concepts[10].display_name | Mathematical optimization |
| concepts[11].id | https://openalex.org/C154945302 |
| concepts[11].level | 1 |
| concepts[11].score | 0.3019440770149231 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[11].display_name | Artificial intelligence |
| concepts[12].id | https://openalex.org/C11413529 |
| concepts[12].level | 1 |
| concepts[12].score | 0.23180216550827026 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[12].display_name | Algorithm |
| concepts[13].id | https://openalex.org/C163258240 |
| concepts[13].level | 2 |
| concepts[13].score | 0.2248893678188324 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q25342 |
| concepts[13].display_name | Power (physics) |
| concepts[14].id | https://openalex.org/C31258907 |
| concepts[14].level | 1 |
| concepts[14].score | 0.19714072346687317 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q1301371 |
| concepts[14].display_name | Computer network |
| concepts[15].id | https://openalex.org/C33923547 |
| concepts[15].level | 0 |
| concepts[15].score | 0.0 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[15].display_name | Mathematics |
| concepts[16].id | https://openalex.org/C62520636 |
| concepts[16].level | 1 |
| concepts[16].score | 0.0 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q944 |
| concepts[16].display_name | Quantum mechanics |
| concepts[17].id | https://openalex.org/C121332964 |
| concepts[17].level | 0 |
| concepts[17].score | 0.0 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q413 |
| concepts[17].display_name | Physics |
| concepts[18].id | https://openalex.org/C76155785 |
| concepts[18].level | 1 |
| concepts[18].score | 0.0 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q418 |
| concepts[18].display_name | Telecommunications |
| keywords[0].id | https://openalex.org/keywords/computer-science |
| keywords[0].score | 0.82724529504776 |
| keywords[0].display_name | Computer science |
| keywords[1].id | https://openalex.org/keywords/reinforcement-learning |
| keywords[1].score | 0.7160155773162842 |
| keywords[1].display_name | Reinforcement learning |
| keywords[2].id | https://openalex.org/keywords/latency |
| keywords[2].score | 0.6306509375572205 |
| keywords[2].display_name | Latency (audio) |
| keywords[3].id | https://openalex.org/keywords/network-packet |
| keywords[3].score | 0.5822203159332275 |
| keywords[3].display_name | Network packet |
| keywords[4].id | https://openalex.org/keywords/deep-learning |
| keywords[4].score | 0.4729616045951843 |
| keywords[4].display_name | Deep learning |
| keywords[5].id | https://openalex.org/keywords/scheduling |
| keywords[5].score | 0.4657132625579834 |
| keywords[5].display_name | Scheduling (production processes) |
| keywords[6].id | https://openalex.org/keywords/reliability |
| keywords[6].score | 0.4618344306945801 |
| keywords[6].display_name | Reliability (semiconductor) |
| keywords[7].id | https://openalex.org/keywords/optimization-problem |
| keywords[7].score | 0.4137353003025055 |
| keywords[7].display_name | Optimization problem |
| keywords[8].id | https://openalex.org/keywords/distributed-computing |
| keywords[8].score | 0.3784952163696289 |
| keywords[8].display_name | Distributed computing |
| keywords[9].id | https://openalex.org/keywords/real-time-computing |
| keywords[9].score | 0.3743666410446167 |
| keywords[9].display_name | Real-time computing |
| keywords[10].id | https://openalex.org/keywords/mathematical-optimization |
| keywords[10].score | 0.3050065338611603 |
| keywords[10].display_name | Mathematical optimization |
| keywords[11].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[11].score | 0.3019440770149231 |
| keywords[11].display_name | Artificial intelligence |
| keywords[12].id | https://openalex.org/keywords/algorithm |
| keywords[12].score | 0.23180216550827026 |
| keywords[12].display_name | Algorithm |
| keywords[13].id | https://openalex.org/keywords/power |
| keywords[13].score | 0.2248893678188324 |
| keywords[13].display_name | Power (physics) |
| keywords[14].id | https://openalex.org/keywords/computer-network |
| keywords[14].score | 0.19714072346687317 |
| keywords[14].display_name | Computer network |
| language | en |
| locations[0].id | doi:10.1109/access.2022.3170447 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S2485537415 |
| locations[0].source.issn | 2169-3536 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2169-3536 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | IEEE Access |
| locations[0].source.host_organization | https://openalex.org/P4310319808 |
| locations[0].source.host_organization_name | Institute of Electrical and Electronics Engineers |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310319808 |
| locations[0].source.host_organization_lineage_names | Institute of Electrical and Electronics Engineers |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://ieeexplore.ieee.org/ielx7/6287639/9668973/09762938.pdf |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | IEEE Access |
| locations[0].landing_page_url | https://doi.org/10.1109/access.2022.3170447 |
| locations[1].id | pmh:oai:doaj.org/article:765453b85abe40a2b2b755baffb63e1e |
| locations[1].is_oa | True |
| locations[1].source.id | https://openalex.org/S4306401280 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[1].source.host_organization | |
| locations[1].source.host_organization_name | |
| locations[1].license | cc-by-sa |
| locations[1].pdf_url | |
| locations[1].version | submittedVersion |
| locations[1].raw_type | article |
| locations[1].license_id | https://openalex.org/licenses/cc-by-sa |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | IEEE Access, Vol 10, Pp 50662-50676 (2022) |
| locations[1].landing_page_url | https://doaj.org/article/765453b85abe40a2b2b755baffb63e1e |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5042702804 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-5100-818X |
| authorships[0].author.display_name | Adeeb Salh |
| authorships[0].countries | MY, SA |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I930072361 |
| authorships[0].affiliations[0].raw_affiliation_string | Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor, Malaysia |
| authorships[0].affiliations[1].institution_ids | https://openalex.org/I72264486 |
| authorships[0].affiliations[1].raw_affiliation_string | Department of Electrical Engineering, University of Tabuk, Tabuk, Saudi Arabia |
| authorships[0].institutions[0].id | https://openalex.org/I930072361 |
| authorships[0].institutions[0].ror | https://ror.org/01c5wha71 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I930072361 |
| authorships[0].institutions[0].country_code | MY |
| authorships[0].institutions[0].display_name | Tun Hussein Onn University of Malaysia |
| authorships[0].institutions[1].id | https://openalex.org/I72264486 |
| authorships[0].institutions[1].ror | https://ror.org/04yej8x59 |
| authorships[0].institutions[1].type | education |
| authorships[0].institutions[1].lineage | https://openalex.org/I72264486 |
| authorships[0].institutions[1].country_code | SA |
| authorships[0].institutions[1].display_name | University of Tabuk |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Adeeb Salh |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Department of Electrical Engineering, University of Tabuk, Tabuk, Saudi Arabia, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor, Malaysia |
| authorships[1].author.id | https://openalex.org/A5066783464 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-0958-4474 |
| authorships[1].author.display_name | Lukman Audah |
| authorships[1].countries | MY |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I930072361 |
| authorships[1].affiliations[0].raw_affiliation_string | Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor, Malaysia |
| authorships[1].institutions[0].id | https://openalex.org/I930072361 |
| authorships[1].institutions[0].ror | https://ror.org/01c5wha71 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I930072361 |
| authorships[1].institutions[0].country_code | MY |
| authorships[1].institutions[0].display_name | Tun Hussein Onn University of Malaysia |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Lukman Audah |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor, Malaysia |
| authorships[2].author.id | https://openalex.org/A5081140044 |
| authorships[2].author.orcid | https://orcid.org/0000-0002-5706-174X |
| authorships[2].author.display_name | Kwang Soon Kim |
| authorships[2].countries | KR |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I193775966 |
| authorships[2].affiliations[0].raw_affiliation_string | School of Electrical & Electronics Engineering, Yonsei University, Seodaemun-gu, Seoul, South Korea |
| authorships[2].institutions[0].id | https://openalex.org/I193775966 |
| authorships[2].institutions[0].ror | https://ror.org/01wjejq96 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I193775966 |
| authorships[2].institutions[0].country_code | KR |
| authorships[2].institutions[0].display_name | Yonsei University |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Kwang Soon Kim |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | School of Electrical & Electronics Engineering, Yonsei University, Seodaemun-gu, Seoul, South Korea |
| authorships[3].author.id | https://openalex.org/A5012786887 |
| authorships[3].author.orcid | https://orcid.org/0000-0003-2857-6979 |
| authorships[3].author.display_name | Saeed Hamood Alsamhi |
| authorships[3].countries | IE, YE |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I78137547 |
| authorships[3].affiliations[0].raw_affiliation_string | Faculty of Engineering, IBB University, Ibb, Yemen |
| authorships[3].affiliations[1].institution_ids | https://openalex.org/I4210095504 |
| authorships[3].affiliations[1].raw_affiliation_string | SRI, Technical University of the Shannon: Midlands Midwest, Athlone, Ireland |
| authorships[3].institutions[0].id | https://openalex.org/I4210095504 |
| authorships[3].institutions[0].ror | https://ror.org/00rve9x39 |
| authorships[3].institutions[0].type | facility |
| authorships[3].institutions[0].lineage | https://openalex.org/I4210095504 |
| authorships[3].institutions[0].country_code | IE |
| authorships[3].institutions[0].display_name | Shannon Applied Biotechnology Centre |
| authorships[3].institutions[1].id | https://openalex.org/I78137547 |
| authorships[3].institutions[1].ror | https://ror.org/00fhcxc56 |
| authorships[3].institutions[1].type | education |
| authorships[3].institutions[1].lineage | https://openalex.org/I78137547 |
| authorships[3].institutions[1].country_code | YE |
| authorships[3].institutions[1].display_name | Ibb University |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Saeed Hamood Alsamhi |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Faculty of Engineering, IBB University, Ibb, Yemen, SRI, Technical University of the Shannon: Midlands Midwest, Athlone, Ireland |
| authorships[4].author.id | https://openalex.org/A5039678928 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-5955-8864 |
| authorships[4].author.display_name | Mohammed A. Alhartomi |
| authorships[4].countries | SA |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I72264486 |
| authorships[4].affiliations[0].raw_affiliation_string | Department of Electrical Engineering, University of Tabuk, Tabuk, Saudi Arabia |
| authorships[4].institutions[0].id | https://openalex.org/I72264486 |
| authorships[4].institutions[0].ror | https://ror.org/04yej8x59 |
| authorships[4].institutions[0].type | education |
| authorships[4].institutions[0].lineage | https://openalex.org/I72264486 |
| authorships[4].institutions[0].country_code | SA |
| authorships[4].institutions[0].display_name | University of Tabuk |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Mohammed A. Alhartomi |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | Department of Electrical Engineering, University of Tabuk, Tabuk, Saudi Arabia |
| authorships[5].author.id | https://openalex.org/A5014834110 |
| authorships[5].author.orcid | https://orcid.org/0000-0003-0623-2286 |
| authorships[5].author.display_name | Qazwan Abdullah |
| authorships[5].countries | MY |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I930072361 |
| authorships[5].affiliations[0].raw_affiliation_string | Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor, Malaysia |
| authorships[5].affiliations[1].institution_ids | https://openalex.org/I32589535 |
| authorships[5].affiliations[1].raw_affiliation_string | Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia |
| authorships[5].institutions[0].id | https://openalex.org/I32589535 |
| authorships[5].institutions[0].ror | https://ror.org/01xb6rs26 |
| authorships[5].institutions[0].type | education |
| authorships[5].institutions[0].lineage | https://openalex.org/I32589535 |
| authorships[5].institutions[0].country_code | MY |
| authorships[5].institutions[0].display_name | Technical University of Malaysia Malacca |
| authorships[5].institutions[1].id | https://openalex.org/I930072361 |
| authorships[5].institutions[1].ror | https://ror.org/01c5wha71 |
| authorships[5].institutions[1].type | education |
| authorships[5].institutions[1].lineage | https://openalex.org/I930072361 |
| authorships[5].institutions[1].country_code | MY |
| authorships[5].institutions[1].display_name | Tun Hussein Onn University of Malaysia |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Qazwan Abdullah |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | Faculty of Electrical Engineering, Universiti Teknikal Malaysia Melaka, Durian Tunggal, Malaysia, Faculty of Electrical and Electronic Engineering, Universiti Tun Hussein Onn Malaysia, Parit Raja, Batu Pahat, Johor, Malaysia |
| authorships[6].author.id | https://openalex.org/A5011625447 |
| authorships[6].author.orcid | https://orcid.org/0000-0002-1291-055X |
| authorships[6].author.display_name | Faris A. Almalki |
| authorships[6].countries | SA |
| authorships[6].affiliations[0].institution_ids | https://openalex.org/I179331831 |
| authorships[6].affiliations[0].raw_affiliation_string | Department of Computer Engineering, College of Computers and Information Technology, Taif University, Taif, Saudi Arabia |
| authorships[6].institutions[0].id | https://openalex.org/I179331831 |
| authorships[6].institutions[0].ror | https://ror.org/014g1a453 |
| authorships[6].institutions[0].type | education |
| authorships[6].institutions[0].lineage | https://openalex.org/I179331831 |
| authorships[6].institutions[0].country_code | SA |
| authorships[6].institutions[0].display_name | Taif University |
| authorships[6].author_position | middle |
| authorships[6].raw_author_name | Faris A. Almalki |
| authorships[6].is_corresponding | False |
| authorships[6].raw_affiliation_strings | Department of Computer Engineering, College of Computers and Information Technology, Taif University, Taif, Saudi Arabia |
| authorships[7].author.id | https://openalex.org/A5016097715 |
| authorships[7].author.orcid | https://orcid.org/0000-0002-7582-4480 |
| authorships[7].author.display_name | Haneen Algethami |
| authorships[7].countries | SA |
| authorships[7].affiliations[0].institution_ids | https://openalex.org/I179331831 |
| authorships[7].affiliations[0].raw_affiliation_string | Department of Computer Science, College of Computers and Information Technology, Taif University, Taif, Saudi Arabia |
| authorships[7].institutions[0].id | https://openalex.org/I179331831 |
| authorships[7].institutions[0].ror | https://ror.org/014g1a453 |
| authorships[7].institutions[0].type | education |
| authorships[7].institutions[0].lineage | https://openalex.org/I179331831 |
| authorships[7].institutions[0].country_code | SA |
| authorships[7].institutions[0].display_name | Taif University |
| authorships[7].author_position | last |
| authorships[7].raw_author_name | Haneen Algethami |
| authorships[7].is_corresponding | False |
| authorships[7].raw_affiliation_strings | Department of Computer Science, College of Computers and Information Technology, Taif University, Taif, Saudi Arabia |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://ieeexplore.ieee.org/ielx7/6287639/9668973/09762938.pdf |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Refiner GAN Algorithmically Enabled Deep-RL for Guaranteed Traffic Packets in Real-Time URLLC B5G Communication Systems |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10964 |
| primary_topic.field.id | https://openalex.org/fields/22 |
| primary_topic.field.display_name | Engineering |
| primary_topic.score | 0.9995999932289124 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2208 |
| primary_topic.subfield.display_name | Electrical and Electronic Engineering |
| primary_topic.display_name | Wireless Communication Security Techniques |
| related_works | https://openalex.org/W4362501864, https://openalex.org/W4306904969, https://openalex.org/W4380318855, https://openalex.org/W2138720691, https://openalex.org/W2031695474, https://openalex.org/W2586732548, https://openalex.org/W3049728571, https://openalex.org/W20361778, https://openalex.org/W2024136090, https://openalex.org/W4375867731 |
| cited_by_count | 27 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 4 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 5 |
| counts_by_year[2].year | 2023 |
| counts_by_year[2].cited_by_count | 8 |
| counts_by_year[3].year | 2022 |
| counts_by_year[3].cited_by_count | 10 |
| locations_count | 2 |
| best_oa_location.id | doi:10.1109/access.2022.3170447 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S2485537415 |
| best_oa_location.source.issn | 2169-3536 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2169-3536 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | IEEE Access |
| best_oa_location.source.host_organization | https://openalex.org/P4310319808 |
| best_oa_location.source.host_organization_name | Institute of Electrical and Electronics Engineers |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310319808 |
| best_oa_location.source.host_organization_lineage_names | Institute of Electrical and Electronics Engineers |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://ieeexplore.ieee.org/ielx7/6287639/9668973/09762938.pdf |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | IEEE Access |
| best_oa_location.landing_page_url | https://doi.org/10.1109/access.2022.3170447 |
| primary_location.id | doi:10.1109/access.2022.3170447 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S2485537415 |
| primary_location.source.issn | 2169-3536 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2169-3536 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | IEEE Access |
| primary_location.source.host_organization | https://openalex.org/P4310319808 |
| primary_location.source.host_organization_name | Institute of Electrical and Electronics Engineers |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310319808 |
| primary_location.source.host_organization_lineage_names | Institute of Electrical and Electronics Engineers |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://ieeexplore.ieee.org/ielx7/6287639/9668973/09762938.pdf |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | IEEE Access |
| primary_location.landing_page_url | https://doi.org/10.1109/access.2022.3170447 |
| publication_date | 2022-01-01 |
| publication_year | 2022 |
| referenced_works | https://openalex.org/W2908464576, https://openalex.org/W3107212184, https://openalex.org/W2914785290, https://openalex.org/W2907063143, https://openalex.org/W3134502172, https://openalex.org/W3033821423, https://openalex.org/W3130344071, https://openalex.org/W2904729448, https://openalex.org/W3142457648, https://openalex.org/W2036533317, https://openalex.org/W2293740706, https://openalex.org/W2900655085, https://openalex.org/W6782174499, https://openalex.org/W3008402949, https://openalex.org/W3112324757, https://openalex.org/W2895615608, https://openalex.org/W2009033028, https://openalex.org/W2808381205, https://openalex.org/W2962908937, https://openalex.org/W3119941528, https://openalex.org/W3002189898, https://openalex.org/W3093951152, https://openalex.org/W3105420554, https://openalex.org/W2761694337, https://openalex.org/W2106864314, https://openalex.org/W2964060933, https://openalex.org/W6761231748, https://openalex.org/W3112739849, https://openalex.org/W2748182655, https://openalex.org/W2962215461, https://openalex.org/W2124982716, https://openalex.org/W2963000651, https://openalex.org/W139596442, https://openalex.org/W2169982856, https://openalex.org/W3096831136, https://openalex.org/W2963709863, https://openalex.org/W7009544117, https://openalex.org/W2968764495, https://openalex.org/W3179018212, https://openalex.org/W3057525668, https://openalex.org/W3104929579 |
| referenced_works_count | 41 |
| abstract_inverted_index.a | 41, 52, 67, 92, 100, 106, 110, 115, 188, 223, 231 |
| abstract_inverted_index.at | 230 |
| abstract_inverted_index.be | 8 |
| abstract_inverted_index.in | 133, 180, 199 |
| abstract_inverted_index.is | 5, 103 |
| abstract_inverted_index.of | 10, 40, 99, 177, 195, 226, 245 |
| abstract_inverted_index.on | 120, 173, 222 |
| abstract_inverted_index.to | 7, 36, 50, 75, 84, 104, 131, 161, 169, 191 |
| abstract_inverted_index.we | 144 |
| abstract_inverted_index.E2E | 59, 243 |
| abstract_inverted_index.GAN | 185, 238 |
| abstract_inverted_index.RB, | 87 |
| abstract_inverted_index.The | 27, 97 |
| abstract_inverted_index.and | 1, 24, 45, 57, 90, 114, 137, 217, 242 |
| abstract_inverted_index.can | 211 |
| abstract_inverted_index.for | 80, 94, 125, 139, 157, 209 |
| abstract_inverted_index.has | 33 |
| abstract_inverted_index.low | 22, 58, 116 |
| abstract_inverted_index.one | 9 |
| abstract_inverted_index.set | 225 |
| abstract_inverted_index.the | 11, 38, 77, 86, 121, 146, 158, 174, 181, 206, 213, 236 |
| abstract_inverted_index.(PA) | 49 |
| abstract_inverted_index.(RB) | 44 |
| abstract_inverted_index.Deep | 28 |
| abstract_inverted_index.This | 64, 183 |
| abstract_inverted_index.been | 34 |
| abstract_inverted_index.cost | 118 |
| abstract_inverted_index.data | 164, 171, 196 |
| abstract_inverted_index.deep | 219 |
| abstract_inverted_index.good | 107 |
| abstract_inverted_index.high | 53, 166 |
| abstract_inverted_index.less | 246 |
| abstract_inverted_index.most | 12 |
| abstract_inverted_index.need | 130 |
| abstract_inverted_index.omit | 212 |
| abstract_inverted_index.rate | 62, 82, 113 |
| abstract_inverted_index.real | 170, 228 |
| abstract_inverted_index.than | 247 |
| abstract_inverted_index.that | 152, 205 |
| abstract_inverted_index.time | 216 |
| abstract_inverted_index.used | 198 |
| abstract_inverted_index.with | 20, 109, 165 |
| abstract_inverted_index.(B5G) | 17 |
| abstract_inverted_index.(E2E) | 55 |
| abstract_inverted_index.Block | 43 |
| abstract_inverted_index.PGACL | 101 |
| abstract_inverted_index.Power | 47 |
| abstract_inverted_index.URLLC | 95, 128 |
| abstract_inverted_index.agent | 160 |
| abstract_inverted_index.apply | 153 |
| abstract_inverted_index.based | 172, 221 |
| abstract_inverted_index.every | 126 |
| abstract_inverted_index.large | 193 |
| abstract_inverted_index.novel | 68 |
| abstract_inverted_index.paper | 65 |
| abstract_inverted_index.short | 233 |
| abstract_inverted_index.solve | 85 |
| abstract_inverted_index.space | 124 |
| abstract_inverted_index.time. | 234 |
| abstract_inverted_index.under | 61 |
| abstract_inverted_index.user. | 127 |
| abstract_inverted_index.(GANs) | 151 |
| abstract_inverted_index.1.4ms. | 248 |
| abstract_inverted_index.Beyond | 15 |
| abstract_inverted_index.Policy | 69 |
| abstract_inverted_index.action | 123 |
| abstract_inverted_index.closer | 111 |
| abstract_inverted_index.enough | 154 |
| abstract_inverted_index.events | 156, 179 |
| abstract_inverted_index.highly | 134 |
| abstract_inverted_index.method | 186 |
| abstract_inverted_index.number | 176 |
| abstract_inverted_index.policy | 78, 108 |
| abstract_inverted_index.power, | 89 |
| abstract_inverted_index.showed | 204 |
| abstract_inverted_index.(PGACL) | 73 |
| abstract_inverted_index.(URLLC) | 4 |
| abstract_inverted_index.account | 138 |
| abstract_inverted_index.amounts | 194 |
| abstract_inverted_index.applied | 35 |
| abstract_inverted_index.deep-RL | 159, 189, 208 |
| abstract_inverted_index.develop | 218 |
| abstract_inverted_index.enables | 187 |
| abstract_inverted_index.extreme | 140, 155, 178 |
| abstract_inverted_index.latency | 23, 60, 244 |
| abstract_inverted_index.network | 141 |
| abstract_inverted_index.operate | 132 |
| abstract_inverted_index.optimal | 81 |
| abstract_inverted_index.predict | 37 |
| abstract_inverted_index.provide | 105 |
| abstract_inverted_index.purpose | 98 |
| abstract_inverted_index.reduced | 122 |
| abstract_inverted_index.refiner | 147, 184, 237 |
| abstract_inverted_index.results | 203 |
| abstract_inverted_index.similar | 168 |
| abstract_inverted_index.systems | 129, 136 |
| abstract_inverted_index.traffic | 229 |
| abstract_inverted_index.Learning | 30, 72 |
| abstract_inverted_index.Networks | 150 |
| abstract_inverted_index.Resource | 42 |
| abstract_inverted_index.approach | 190 |
| abstract_inverted_index.cellular | 18 |
| abstract_inverted_index.critical | 13 |
| abstract_inverted_index.dataset. | 182 |
| abstract_inverted_index.expected | 6 |
| abstract_inverted_index.generate | 162, 192 |
| abstract_inverted_index.gradient | 79 |
| abstract_inverted_index.learning | 220 |
| abstract_inverted_index.minimize | 46, 88 |
| abstract_inverted_index.networks | 19 |
| abstract_inverted_index.optimize | 76 |
| abstract_inverted_index.proposed | 145, 207 |
| abstract_inverted_index.proposes | 66 |
| abstract_inverted_index.reliable | 135 |
| abstract_inverted_index.solution | 93 |
| abstract_inverted_index.training | 215 |
| abstract_inverted_index.(deep-RL) | 31 |
| abstract_inverted_index.algorithm | 74, 102 |
| abstract_inverted_index.depending | 119 |
| abstract_inverted_index.framework | 32 |
| abstract_inverted_index.guarantee | 51, 91 |
| abstract_inverted_index.real-time | 200 |
| abstract_inverted_index.regulated | 175 |
| abstract_inverted_index.stringent | 21 |
| abstract_inverted_index.synthetic | 163 |
| abstract_inverted_index.transient | 214 |
| abstract_inverted_index.unlabeled | 227 |
| abstract_inverted_index.Allocation | 48 |
| abstract_inverted_index.End-to-End | 54 |
| abstract_inverted_index.Generative | 148 |
| abstract_inverted_index.Simulation | 202 |
| abstract_inverted_index.Therefore, | 143 |
| abstract_inverted_index.allocation | 83 |
| abstract_inverted_index.controlled | 224 |
| abstract_inverted_index.relatively | 232 |
| abstract_inverted_index.Adversarial | 149 |
| abstract_inverted_index.Low-latency | 2 |
| abstract_inverted_index.conditions. | 142 |
| abstract_inverted_index.convergence | 112 |
| abstract_inverted_index.operations. | 201 |
| abstract_inverted_index.practically | 197 |
| abstract_inverted_index.refiner-GAN | 210 |
| abstract_inverted_index.reliability | 56, 167, 241 |
| abstract_inverted_index.scheduling. | 96 |
| abstract_inverted_index.Actor-Critic | 71 |
| abstract_inverted_index.Furthermore, | 235 |
| abstract_inverted_index.constraints. | 63 |
| abstract_inverted_index.demonstrated | 239 |
| abstract_inverted_index.optimization | 39 |
| abstract_inverted_index.Reinforcement | 29 |
| abstract_inverted_index.computational | 117 |
| abstract_inverted_index.requirements. | 26 |
| abstract_inverted_index.Communications | 3 |
| abstract_inverted_index.Gradient-based | 70 |
| abstract_inverted_index.Ultra-reliable | 0 |
| abstract_inverted_index.99.9999% | 240 |
| abstract_inverted_index.characteristics | 14 |
| abstract_inverted_index.fifth-Generation | 16 |
| abstract_inverted_index.high-reliability | 25 |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 97 |
| countries_distinct_count | 5 |
| institutions_distinct_count | 8 |
| citation_normalized_percentile.value | 0.90267219 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |