[Retracted] An Ensemble Deep Learning Model for Automatic Modulation Classification in 5G and Beyond IoT Networks Article Swipe
Chirag Roy
,
Satyendra Singh Yadav
,
Vipin Pal
,
Mangal Singh
,
Sarat Kumar Patra
,
G. R. Sinha
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1155/2021/5047355
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1155/2021/5047355
With rapid advancement in artificial intelligence (AI) and machine learning (ML), automatic modulation classification (AMC) using deep learning (DL) techniques has become very popular. This is even more relevant for Internet of things (IoT)‐assisted wireless systems. This paper presents a lightweight, ensemble model with convolution, long short term memory (LSTM), and gated recurrent unit (GRU) layers. The proposed model is termed as deep recurrent convoluted network with additional gated layer (DRCaG). It has been tested on a dataset derived from the RadioML2016(b) and comprises of 8 different modulation types named as BPSK, QPSK, 8‐PSK, 16‐QAM, 4‐PAM, CPFSK, GFSK, and WBFM. The performance of the proposed model has been presented through extensive simulation in terms of training loss, accuracy, and confusion matrix with variable signal to noise ratio (SNR) ranging from −20 dB to +20 dB and it demonstrates the superiority of DRCaG vis‐a‐vis existing ones.
Related Topics
Concepts
Computer science
Deep learning
Artificial intelligence
Phase-shift keying
Modulation (music)
Ranging
Convolution (computer science)
Pattern recognition (psychology)
Channel (broadcasting)
Speech recognition
Machine learning
Bit error rate
Artificial neural network
Telecommunications
Aesthetics
Philosophy
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1155/2021/5047355
- https://downloads.hindawi.com/journals/cin/2021/5047355.pdf
- OA Status
- hybrid
- Cited By
- 12
- References
- 24
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4200032188
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4200032188Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1155/2021/5047355Digital Object Identifier
- Title
-
[Retracted] An Ensemble Deep Learning Model for Automatic Modulation Classification in 5G and Beyond IoT NetworksWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-01-01Full publication date if available
- Authors
-
Chirag Roy, Satyendra Singh Yadav, Vipin Pal, Mangal Singh, Sarat Kumar Patra, G. R. SinhaList of authors in order
- Landing page
-
https://doi.org/10.1155/2021/5047355Publisher landing page
- PDF URL
-
https://downloads.hindawi.com/journals/cin/2021/5047355.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
-
https://downloads.hindawi.com/journals/cin/2021/5047355.pdfDirect OA link when available
- Concepts
-
Computer science, Deep learning, Artificial intelligence, Phase-shift keying, Modulation (music), Ranging, Convolution (computer science), Pattern recognition (psychology), Channel (broadcasting), Speech recognition, Machine learning, Bit error rate, Artificial neural network, Telecommunications, Aesthetics, PhilosophyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
12Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2, 2024: 5, 2023: 5Per-year citation counts (last 5 years)
- References (count)
-
24Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4200032188 |
|---|---|
| doi | https://doi.org/10.1155/2021/5047355 |
| ids.doi | https://doi.org/10.1155/2021/5047355 |
| ids.pmid | https://pubmed.ncbi.nlm.nih.gov/34950200 |
| ids.openalex | https://openalex.org/W4200032188 |
| fwci | 1.41103575 |
| mesh[0].qualifier_ui | |
| mesh[0].descriptor_ui | D001185 |
| mesh[0].is_major_topic | False |
| mesh[0].qualifier_name | |
| mesh[0].descriptor_name | Artificial Intelligence |
| mesh[1].qualifier_ui | |
| mesh[1].descriptor_ui | D000077321 |
| mesh[1].is_major_topic | True |
| mesh[1].qualifier_name | |
| mesh[1].descriptor_name | Deep Learning |
| mesh[2].qualifier_ui | |
| mesh[2].descriptor_ui | D000080487 |
| mesh[2].is_major_topic | True |
| mesh[2].qualifier_name | |
| mesh[2].descriptor_name | Internet of Things |
| mesh[3].qualifier_ui | |
| mesh[3].descriptor_ui | D000069550 |
| mesh[3].is_major_topic | False |
| mesh[3].qualifier_name | |
| mesh[3].descriptor_name | Machine Learning |
| mesh[4].qualifier_ui | |
| mesh[4].descriptor_ui | D016571 |
| mesh[4].is_major_topic | False |
| mesh[4].qualifier_name | |
| mesh[4].descriptor_name | Neural Networks, Computer |
| mesh[5].qualifier_ui | |
| mesh[5].descriptor_ui | D001185 |
| mesh[5].is_major_topic | False |
| mesh[5].qualifier_name | |
| mesh[5].descriptor_name | Artificial Intelligence |
| mesh[6].qualifier_ui | |
| mesh[6].descriptor_ui | D000077321 |
| mesh[6].is_major_topic | True |
| mesh[6].qualifier_name | |
| mesh[6].descriptor_name | Deep Learning |
| mesh[7].qualifier_ui | |
| mesh[7].descriptor_ui | D000080487 |
| mesh[7].is_major_topic | True |
| mesh[7].qualifier_name | |
| mesh[7].descriptor_name | Internet of Things |
| mesh[8].qualifier_ui | |
| mesh[8].descriptor_ui | D000069550 |
| mesh[8].is_major_topic | False |
| mesh[8].qualifier_name | |
| mesh[8].descriptor_name | Machine Learning |
| mesh[9].qualifier_ui | |
| mesh[9].descriptor_ui | D016571 |
| mesh[9].is_major_topic | False |
| mesh[9].qualifier_name | |
| mesh[9].descriptor_name | Neural Networks, Computer |
| mesh[10].qualifier_ui | |
| mesh[10].descriptor_ui | D001185 |
| mesh[10].is_major_topic | False |
| mesh[10].qualifier_name | |
| mesh[10].descriptor_name | Artificial Intelligence |
| mesh[11].qualifier_ui | |
| mesh[11].descriptor_ui | D000077321 |
| mesh[11].is_major_topic | True |
| mesh[11].qualifier_name | |
| mesh[11].descriptor_name | Deep Learning |
| mesh[12].qualifier_ui | |
| mesh[12].descriptor_ui | D000080487 |
| mesh[12].is_major_topic | True |
| mesh[12].qualifier_name | |
| mesh[12].descriptor_name | Internet of Things |
| mesh[13].qualifier_ui | |
| mesh[13].descriptor_ui | D000069550 |
| mesh[13].is_major_topic | False |
| mesh[13].qualifier_name | |
| mesh[13].descriptor_name | Machine Learning |
| mesh[14].qualifier_ui | |
| mesh[14].descriptor_ui | D016571 |
| mesh[14].is_major_topic | False |
| mesh[14].qualifier_name | |
| mesh[14].descriptor_name | Neural Networks, Computer |
| type | article |
| title | [Retracted] An Ensemble Deep Learning Model for Automatic Modulation Classification in 5G and Beyond IoT Networks |
| biblio.issue | 1 |
| biblio.volume | 2021 |
| biblio.last_page | 5047355 |
| biblio.first_page | 5047355 |
| topics[0].id | https://openalex.org/T12131 |
| topics[0].field.id | https://openalex.org/fields/17 |
| topics[0].field.display_name | Computer Science |
| topics[0].score | 0.9998999834060669 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1702 |
| topics[0].subfield.display_name | Artificial Intelligence |
| topics[0].display_name | Wireless Signal Modulation Classification |
| topics[1].id | https://openalex.org/T10207 |
| topics[1].field.id | https://openalex.org/fields/13 |
| topics[1].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[1].score | 0.95169997215271 |
| topics[1].domain.id | https://openalex.org/domains/1 |
| topics[1].domain.display_name | Life Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1312 |
| topics[1].subfield.display_name | Molecular Biology |
| topics[1].display_name | Advanced biosensing and bioanalysis techniques |
| is_xpac | False |
| apc_list.value | 2100 |
| apc_list.currency | USD |
| apc_list.value_usd | 2100 |
| apc_paid.value | 2100 |
| apc_paid.currency | USD |
| apc_paid.value_usd | 2100 |
| concepts[0].id | https://openalex.org/C41008148 |
| concepts[0].level | 0 |
| concepts[0].score | 0.7641206979751587 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[0].display_name | Computer science |
| concepts[1].id | https://openalex.org/C108583219 |
| concepts[1].level | 2 |
| concepts[1].score | 0.6193352341651917 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q197536 |
| concepts[1].display_name | Deep learning |
| concepts[2].id | https://openalex.org/C154945302 |
| concepts[2].level | 1 |
| concepts[2].score | 0.6188051700592041 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[2].display_name | Artificial intelligence |
| concepts[3].id | https://openalex.org/C186378180 |
| concepts[3].level | 4 |
| concepts[3].score | 0.5495634078979492 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q4874866 |
| concepts[3].display_name | Phase-shift keying |
| concepts[4].id | https://openalex.org/C123079801 |
| concepts[4].level | 2 |
| concepts[4].score | 0.5221543312072754 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q750240 |
| concepts[4].display_name | Modulation (music) |
| concepts[5].id | https://openalex.org/C115051666 |
| concepts[5].level | 2 |
| concepts[5].score | 0.4478864073753357 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q6522493 |
| concepts[5].display_name | Ranging |
| concepts[6].id | https://openalex.org/C45347329 |
| concepts[6].level | 3 |
| concepts[6].score | 0.42481765151023865 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q5166604 |
| concepts[6].display_name | Convolution (computer science) |
| concepts[7].id | https://openalex.org/C153180895 |
| concepts[7].level | 2 |
| concepts[7].score | 0.38415762782096863 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q7148389 |
| concepts[7].display_name | Pattern recognition (psychology) |
| concepts[8].id | https://openalex.org/C127162648 |
| concepts[8].level | 2 |
| concepts[8].score | 0.361189603805542 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q16858953 |
| concepts[8].display_name | Channel (broadcasting) |
| concepts[9].id | https://openalex.org/C28490314 |
| concepts[9].level | 1 |
| concepts[9].score | 0.34765195846557617 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q189436 |
| concepts[9].display_name | Speech recognition |
| concepts[10].id | https://openalex.org/C119857082 |
| concepts[10].level | 1 |
| concepts[10].score | 0.32845139503479004 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q2539 |
| concepts[10].display_name | Machine learning |
| concepts[11].id | https://openalex.org/C56296756 |
| concepts[11].level | 3 |
| concepts[11].score | 0.22049501538276672 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q840922 |
| concepts[11].display_name | Bit error rate |
| concepts[12].id | https://openalex.org/C50644808 |
| concepts[12].level | 2 |
| concepts[12].score | 0.19745594263076782 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q192776 |
| concepts[12].display_name | Artificial neural network |
| concepts[13].id | https://openalex.org/C76155785 |
| concepts[13].level | 1 |
| concepts[13].score | 0.19676244258880615 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q418 |
| concepts[13].display_name | Telecommunications |
| concepts[14].id | https://openalex.org/C107038049 |
| concepts[14].level | 1 |
| concepts[14].score | 0.0 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q35986 |
| concepts[14].display_name | Aesthetics |
| concepts[15].id | https://openalex.org/C138885662 |
| concepts[15].level | 0 |
| concepts[15].score | 0.0 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q5891 |
| concepts[15].display_name | Philosophy |
| keywords[0].id | https://openalex.org/keywords/computer-science |
| keywords[0].score | 0.7641206979751587 |
| keywords[0].display_name | Computer science |
| keywords[1].id | https://openalex.org/keywords/deep-learning |
| keywords[1].score | 0.6193352341651917 |
| keywords[1].display_name | Deep learning |
| keywords[2].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[2].score | 0.6188051700592041 |
| keywords[2].display_name | Artificial intelligence |
| keywords[3].id | https://openalex.org/keywords/phase-shift-keying |
| keywords[3].score | 0.5495634078979492 |
| keywords[3].display_name | Phase-shift keying |
| keywords[4].id | https://openalex.org/keywords/modulation |
| keywords[4].score | 0.5221543312072754 |
| keywords[4].display_name | Modulation (music) |
| keywords[5].id | https://openalex.org/keywords/ranging |
| keywords[5].score | 0.4478864073753357 |
| keywords[5].display_name | Ranging |
| keywords[6].id | https://openalex.org/keywords/convolution |
| keywords[6].score | 0.42481765151023865 |
| keywords[6].display_name | Convolution (computer science) |
| keywords[7].id | https://openalex.org/keywords/pattern-recognition |
| keywords[7].score | 0.38415762782096863 |
| keywords[7].display_name | Pattern recognition (psychology) |
| keywords[8].id | https://openalex.org/keywords/channel |
| keywords[8].score | 0.361189603805542 |
| keywords[8].display_name | Channel (broadcasting) |
| keywords[9].id | https://openalex.org/keywords/speech-recognition |
| keywords[9].score | 0.34765195846557617 |
| keywords[9].display_name | Speech recognition |
| keywords[10].id | https://openalex.org/keywords/machine-learning |
| keywords[10].score | 0.32845139503479004 |
| keywords[10].display_name | Machine learning |
| keywords[11].id | https://openalex.org/keywords/bit-error-rate |
| keywords[11].score | 0.22049501538276672 |
| keywords[11].display_name | Bit error rate |
| keywords[12].id | https://openalex.org/keywords/artificial-neural-network |
| keywords[12].score | 0.19745594263076782 |
| keywords[12].display_name | Artificial neural network |
| keywords[13].id | https://openalex.org/keywords/telecommunications |
| keywords[13].score | 0.19676244258880615 |
| keywords[13].display_name | Telecommunications |
| language | en |
| locations[0].id | doi:10.1155/2021/5047355 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S72372694 |
| locations[0].source.issn | 1687-5265, 1687-5273 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | False |
| locations[0].source.issn_l | 1687-5265 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | Computational Intelligence and Neuroscience |
| locations[0].source.host_organization | https://openalex.org/P4310319869 |
| locations[0].source.host_organization_name | Hindawi Publishing Corporation |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310319869 |
| locations[0].source.host_organization_lineage_names | Hindawi Publishing Corporation |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://downloads.hindawi.com/journals/cin/2021/5047355.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 | Computational Intelligence and Neuroscience |
| locations[0].landing_page_url | https://doi.org/10.1155/2021/5047355 |
| locations[1].id | pmid:34950200 |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306525036 |
| 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 | PubMed |
| locations[1].source.host_organization | https://openalex.org/I1299303238 |
| locations[1].source.host_organization_name | National Institutes of Health |
| locations[1].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | publishedVersion |
| locations[1].raw_type | |
| locations[1].license_id | |
| locations[1].is_accepted | True |
| locations[1].is_published | True |
| locations[1].raw_source_name | Computational intelligence and neuroscience |
| locations[1].landing_page_url | https://pubmed.ncbi.nlm.nih.gov/34950200 |
| locations[2].id | pmh:oai:doaj.org/article:51d964b0195d4d5da83e0bb109559539 |
| locations[2].is_oa | True |
| locations[2].source.id | https://openalex.org/S4306401280 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | False |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[2].source.host_organization | |
| locations[2].source.host_organization_name | |
| locations[2].license | cc-by-sa |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | article |
| locations[2].license_id | https://openalex.org/licenses/cc-by-sa |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | Computational Intelligence and Neuroscience, Vol 2021 (2021) |
| locations[2].landing_page_url | https://doaj.org/article/51d964b0195d4d5da83e0bb109559539 |
| locations[3].id | pmh:oai:pubmedcentral.nih.gov:8691989 |
| locations[3].is_oa | True |
| locations[3].source.id | https://openalex.org/S2764455111 |
| locations[3].source.issn | |
| locations[3].source.type | repository |
| locations[3].source.is_oa | False |
| locations[3].source.issn_l | |
| locations[3].source.is_core | False |
| locations[3].source.is_in_doaj | False |
| locations[3].source.display_name | PubMed Central |
| locations[3].source.host_organization | https://openalex.org/I1299303238 |
| locations[3].source.host_organization_name | National Institutes of Health |
| locations[3].source.host_organization_lineage | https://openalex.org/I1299303238 |
| locations[3].license | other-oa |
| locations[3].pdf_url | |
| locations[3].version | submittedVersion |
| locations[3].raw_type | Text |
| locations[3].license_id | https://openalex.org/licenses/other-oa |
| locations[3].is_accepted | False |
| locations[3].is_published | False |
| locations[3].raw_source_name | Comput Intell Neurosci |
| locations[3].landing_page_url | https://www.ncbi.nlm.nih.gov/pmc/articles/8691989 |
| indexed_in | crossref, doaj, pubmed |
| authorships[0].author.id | https://openalex.org/A5052818595 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | Chirag Roy |
| authorships[0].countries | IN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I9523339 |
| authorships[0].affiliations[0].raw_affiliation_string | Department of Electronics and Communication Engineering, National Institute of Technology, Meghalaya, India |
| authorships[0].institutions[0].id | https://openalex.org/I9523339 |
| authorships[0].institutions[0].ror | https://ror.org/020vd6n84 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I9523339 |
| authorships[0].institutions[0].country_code | IN |
| authorships[0].institutions[0].display_name | National Institute of Technology Meghalaya |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Chirag Roy |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Department of Electronics and Communication Engineering, National Institute of Technology, Meghalaya, India |
| authorships[1].author.id | https://openalex.org/A5032405147 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-7891-6997 |
| authorships[1].author.display_name | Satyendra Singh Yadav |
| authorships[1].countries | IN |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I9523339 |
| authorships[1].affiliations[0].raw_affiliation_string | Department of Electronics and Communication Engineering, National Institute of Technology, Meghalaya, India |
| authorships[1].institutions[0].id | https://openalex.org/I9523339 |
| authorships[1].institutions[0].ror | https://ror.org/020vd6n84 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I9523339 |
| authorships[1].institutions[0].country_code | IN |
| authorships[1].institutions[0].display_name | National Institute of Technology Meghalaya |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Satyendra Singh Yadav |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Department of Electronics and Communication Engineering, National Institute of Technology, Meghalaya, India |
| authorships[2].author.id | https://openalex.org/A5032054973 |
| authorships[2].author.orcid | https://orcid.org/0000-0002-8157-1379 |
| authorships[2].author.display_name | Vipin Pal |
| authorships[2].countries | IN |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I9523339 |
| authorships[2].affiliations[0].raw_affiliation_string | Department of Computer Science and Engineering, National Institute of Technology, Meghalaya, India |
| authorships[2].institutions[0].id | https://openalex.org/I9523339 |
| authorships[2].institutions[0].ror | https://ror.org/020vd6n84 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I9523339 |
| authorships[2].institutions[0].country_code | IN |
| authorships[2].institutions[0].display_name | National Institute of Technology Meghalaya |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Vipin Pal |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Department of Computer Science and Engineering, National Institute of Technology, Meghalaya, India |
| authorships[3].author.id | https://openalex.org/A5062749728 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-0971-657X |
| authorships[3].author.display_name | Mangal Singh |
| authorships[3].countries | IN |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I244572783 |
| authorships[3].affiliations[0].raw_affiliation_string | Department of Electronics and Telecommunication Engineering, Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune, India |
| authorships[3].institutions[0].id | https://openalex.org/I244572783 |
| authorships[3].institutions[0].ror | https://ror.org/005r2ww51 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I244572783 |
| authorships[3].institutions[0].country_code | IN |
| authorships[3].institutions[0].display_name | Symbiosis International University |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Mangal Singh |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Department of Electronics and Telecommunication Engineering, Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune, India |
| authorships[4].author.id | https://openalex.org/A5075822182 |
| authorships[4].author.orcid | https://orcid.org/0000-0002-6188-1302 |
| authorships[4].author.display_name | Sarat Kumar Patra |
| authorships[4].countries | IN |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I4210100893 |
| authorships[4].affiliations[0].raw_affiliation_string | Indian Institute of Information Technology, Vadodara, India |
| authorships[4].institutions[0].id | https://openalex.org/I4210100893 |
| authorships[4].institutions[0].ror | https://ror.org/0163rt176 |
| authorships[4].institutions[0].type | education |
| authorships[4].institutions[0].lineage | https://openalex.org/I4210100893 |
| authorships[4].institutions[0].country_code | IN |
| authorships[4].institutions[0].display_name | Indian Institute of Information Technology Vadodara |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Sarat Kumar Patra |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | Indian Institute of Information Technology, Vadodara, India |
| authorships[5].author.id | https://openalex.org/A5085796013 |
| authorships[5].author.orcid | https://orcid.org/0000-0003-2384-4591 |
| authorships[5].author.display_name | G. R. Sinha |
| authorships[5].countries | MM |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I3132516330 |
| authorships[5].affiliations[0].raw_affiliation_string | Myanmar Institute of Information Technology, Mandalay, Myanmar |
| authorships[5].institutions[0].id | https://openalex.org/I3132516330 |
| authorships[5].institutions[0].ror | https://ror.org/038smxt70 |
| authorships[5].institutions[0].type | education |
| authorships[5].institutions[0].lineage | https://openalex.org/I3132516330 |
| authorships[5].institutions[0].country_code | MM |
| authorships[5].institutions[0].display_name | Myanmar Institute of Information Technology |
| authorships[5].author_position | last |
| authorships[5].raw_author_name | G. R. Sinha |
| authorships[5].is_corresponding | True |
| authorships[5].raw_affiliation_strings | Myanmar Institute of Information Technology, Mandalay, Myanmar |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://downloads.hindawi.com/journals/cin/2021/5047355.pdf |
| open_access.oa_status | hybrid |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | [Retracted] An Ensemble Deep Learning Model for Automatic Modulation Classification in 5G and Beyond IoT Networks |
| has_fulltext | True |
| is_retracted | True |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T12131 |
| primary_topic.field.id | https://openalex.org/fields/17 |
| primary_topic.field.display_name | Computer Science |
| primary_topic.score | 0.9998999834060669 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1702 |
| primary_topic.subfield.display_name | Artificial Intelligence |
| primary_topic.display_name | Wireless Signal Modulation Classification |
| related_works | https://openalex.org/W2783354812, https://openalex.org/W4384112194, https://openalex.org/W2103009189, https://openalex.org/W4312958259, https://openalex.org/W4308259661, https://openalex.org/W4390813131, https://openalex.org/W2349383066, https://openalex.org/W4328132048, https://openalex.org/W1969901537, https://openalex.org/W2119768059 |
| cited_by_count | 12 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 2 |
| 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 | 5 |
| locations_count | 4 |
| best_oa_location.id | doi:10.1155/2021/5047355 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S72372694 |
| best_oa_location.source.issn | 1687-5265, 1687-5273 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | False |
| best_oa_location.source.issn_l | 1687-5265 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | Computational Intelligence and Neuroscience |
| best_oa_location.source.host_organization | https://openalex.org/P4310319869 |
| best_oa_location.source.host_organization_name | Hindawi Publishing Corporation |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310319869 |
| best_oa_location.source.host_organization_lineage_names | Hindawi Publishing Corporation |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://downloads.hindawi.com/journals/cin/2021/5047355.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 | Computational Intelligence and Neuroscience |
| best_oa_location.landing_page_url | https://doi.org/10.1155/2021/5047355 |
| primary_location.id | doi:10.1155/2021/5047355 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S72372694 |
| primary_location.source.issn | 1687-5265, 1687-5273 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | False |
| primary_location.source.issn_l | 1687-5265 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | Computational Intelligence and Neuroscience |
| primary_location.source.host_organization | https://openalex.org/P4310319869 |
| primary_location.source.host_organization_name | Hindawi Publishing Corporation |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310319869 |
| primary_location.source.host_organization_lineage_names | Hindawi Publishing Corporation |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://downloads.hindawi.com/journals/cin/2021/5047355.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 | Computational Intelligence and Neuroscience |
| primary_location.landing_page_url | https://doi.org/10.1155/2021/5047355 |
| publication_date | 2021-01-01 |
| publication_year | 2021 |
| referenced_works | https://openalex.org/W3003174479, https://openalex.org/W2966038277, https://openalex.org/W3048385670, https://openalex.org/W3116996730, https://openalex.org/W3011724393, https://openalex.org/W2272847350, https://openalex.org/W3010976968, https://openalex.org/W3014752979, https://openalex.org/W2803445619, https://openalex.org/W3204369957, https://openalex.org/W3036462559, https://openalex.org/W2947256479, https://openalex.org/W2795250928, https://openalex.org/W2790896200, https://openalex.org/W2609179406, https://openalex.org/W3091886083, https://openalex.org/W2884089434, https://openalex.org/W3022311971, https://openalex.org/W2892154397, https://openalex.org/W3191189689, https://openalex.org/W2586530066, https://openalex.org/W3189419917, https://openalex.org/W4211214838, https://openalex.org/W2909712920 |
| referenced_works_count | 24 |
| abstract_inverted_index.8 | 85 |
| abstract_inverted_index.a | 39, 76 |
| abstract_inverted_index.It | 71 |
| abstract_inverted_index.as | 61, 90 |
| abstract_inverted_index.dB | 131, 134 |
| abstract_inverted_index.in | 3, 112 |
| abstract_inverted_index.is | 25, 59 |
| abstract_inverted_index.it | 136 |
| abstract_inverted_index.of | 31, 84, 102, 114, 140 |
| abstract_inverted_index.on | 75 |
| abstract_inverted_index.to | 124, 132 |
| abstract_inverted_index.+20 | 133 |
| abstract_inverted_index.The | 56, 100 |
| abstract_inverted_index.and | 7, 50, 82, 98, 118, 135 |
| abstract_inverted_index.for | 29 |
| abstract_inverted_index.has | 20, 72, 106 |
| abstract_inverted_index.the | 80, 103, 138 |
| abstract_inverted_index.(AI) | 6 |
| abstract_inverted_index.(DL) | 18 |
| abstract_inverted_index.This | 24, 36 |
| abstract_inverted_index.With | 0 |
| abstract_inverted_index.been | 73, 107 |
| abstract_inverted_index.deep | 16, 62 |
| abstract_inverted_index.even | 26 |
| abstract_inverted_index.from | 79, 129 |
| abstract_inverted_index.long | 45 |
| abstract_inverted_index.more | 27 |
| abstract_inverted_index.term | 47 |
| abstract_inverted_index.unit | 53 |
| abstract_inverted_index.very | 22 |
| abstract_inverted_index.with | 43, 66, 121 |
| abstract_inverted_index.(AMC) | 14 |
| abstract_inverted_index.(GRU) | 54 |
| abstract_inverted_index.(ML), | 10 |
| abstract_inverted_index.(SNR) | 127 |
| abstract_inverted_index.BPSK, | 91 |
| abstract_inverted_index.DRCaG | 141 |
| abstract_inverted_index.GFSK, | 97 |
| abstract_inverted_index.QPSK, | 92 |
| abstract_inverted_index.WBFM. | 99 |
| abstract_inverted_index.gated | 51, 68 |
| abstract_inverted_index.layer | 69 |
| abstract_inverted_index.loss, | 116 |
| abstract_inverted_index.model | 42, 58, 105 |
| abstract_inverted_index.named | 89 |
| abstract_inverted_index.noise | 125 |
| abstract_inverted_index.ones. | 144 |
| abstract_inverted_index.paper | 37 |
| abstract_inverted_index.rapid | 1 |
| abstract_inverted_index.ratio | 126 |
| abstract_inverted_index.short | 46 |
| abstract_inverted_index.terms | 113 |
| abstract_inverted_index.types | 88 |
| abstract_inverted_index.using | 15 |
| abstract_inverted_index.−20 | 130 |
| abstract_inverted_index.CPFSK, | 96 |
| abstract_inverted_index.become | 21 |
| abstract_inverted_index.matrix | 120 |
| abstract_inverted_index.memory | 48 |
| abstract_inverted_index.signal | 123 |
| abstract_inverted_index.termed | 60 |
| abstract_inverted_index.tested | 74 |
| abstract_inverted_index.things | 32 |
| abstract_inverted_index.(LSTM), | 49 |
| abstract_inverted_index.dataset | 77 |
| abstract_inverted_index.derived | 78 |
| abstract_inverted_index.layers. | 55 |
| abstract_inverted_index.machine | 8 |
| abstract_inverted_index.network | 65 |
| abstract_inverted_index.ranging | 128 |
| abstract_inverted_index.through | 109 |
| abstract_inverted_index.(DRCaG). | 70 |
| abstract_inverted_index.4‐PAM, | 95 |
| abstract_inverted_index.8‐PSK, | 93 |
| abstract_inverted_index.Internet | 30 |
| abstract_inverted_index.ensemble | 41 |
| abstract_inverted_index.existing | 143 |
| abstract_inverted_index.learning | 9, 17 |
| abstract_inverted_index.popular. | 23 |
| abstract_inverted_index.presents | 38 |
| abstract_inverted_index.proposed | 57, 104 |
| abstract_inverted_index.relevant | 28 |
| abstract_inverted_index.systems. | 35 |
| abstract_inverted_index.training | 115 |
| abstract_inverted_index.variable | 122 |
| abstract_inverted_index.wireless | 34 |
| abstract_inverted_index.16‐QAM, | 94 |
| abstract_inverted_index.accuracy, | 117 |
| abstract_inverted_index.automatic | 11 |
| abstract_inverted_index.comprises | 83 |
| abstract_inverted_index.confusion | 119 |
| abstract_inverted_index.different | 86 |
| abstract_inverted_index.extensive | 110 |
| abstract_inverted_index.presented | 108 |
| abstract_inverted_index.recurrent | 52, 63 |
| abstract_inverted_index.additional | 67 |
| abstract_inverted_index.artificial | 4 |
| abstract_inverted_index.convoluted | 64 |
| abstract_inverted_index.modulation | 12, 87 |
| abstract_inverted_index.simulation | 111 |
| abstract_inverted_index.techniques | 19 |
| abstract_inverted_index.advancement | 2 |
| abstract_inverted_index.performance | 101 |
| abstract_inverted_index.superiority | 139 |
| abstract_inverted_index.convolution, | 44 |
| abstract_inverted_index.demonstrates | 137 |
| abstract_inverted_index.intelligence | 5 |
| abstract_inverted_index.lightweight, | 40 |
| abstract_inverted_index.vis‐a‐vis | 142 |
| abstract_inverted_index.RadioML2016(b) | 81 |
| abstract_inverted_index.classification | 13 |
| abstract_inverted_index.(IoT)‐assisted | 33 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 95 |
| corresponding_author_ids | https://openalex.org/A5085796013 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 6 |
| corresponding_institution_ids | https://openalex.org/I3132516330 |
| citation_normalized_percentile.value | 0.85522628 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |