{"id":"https://openalex.org/W4362514623","doi":"https://doi.org/10.1109/access.2023.3264230","title":"Deep Learning for Path Loss Prediction at 7 GHz in Urban Environment","display_name":"Deep Learning for Path Loss Prediction at 7 GHz in Urban Environment","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4362514623","doi":"https://doi.org/10.1109/access.2023.3264230","pmid":"https://pubmed.ncbi.nlm.nih.gov/42040234"},"language":"en","primary_location":{"id":"doi:10.1109/access.2023.3264230","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3264230","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10091527.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10091527.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5003918071","display_name":"Thao T. Nguyen","orcid":"https://orcid.org/0000-0001-6232-2214"},"institutions":[{"id":"https://openalex.org/I1321296531","display_name":"National Institute of Standards and Technology","ror":"https://ror.org/05xpvk416","country_code":"US","type":"funder","lineage":["https://openalex.org/I1321296531","https://openalex.org/I1343035065"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Thao T. Nguyen","raw_affiliation_strings":["National Institute of Standards and Technology, Gaithersburg, MD, USA"],"raw_orcid":"https://orcid.org/0000-0001-6232-2214","affiliations":[{"raw_affiliation_string":"National Institute of Standards and Technology, Gaithersburg, MD, USA","institution_ids":["https://openalex.org/I1321296531"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027920617","display_name":"Nadia Yoza-Mitsuishi","orcid":"https://orcid.org/0000-0002-7805-5445"},"institutions":[{"id":"https://openalex.org/I1321296531","display_name":"National Institute of Standards and Technology","ror":"https://ror.org/05xpvk416","country_code":"US","type":"funder","lineage":["https://openalex.org/I1321296531","https://openalex.org/I1343035065"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nadia Yoza-Mitsuishi","raw_affiliation_strings":["National Institute of Standards and Technology, Boulder, CO, USA"],"raw_orcid":"https://orcid.org/0000-0002-7805-5445","affiliations":[{"raw_affiliation_string":"National Institute of Standards and Technology, Boulder, CO, USA","institution_ids":["https://openalex.org/I1321296531"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017038926","display_name":"Raied Caromi","orcid":"https://orcid.org/0000-0002-8273-0642"},"institutions":[{"id":"https://openalex.org/I1321296531","display_name":"National Institute of Standards and Technology","ror":"https://ror.org/05xpvk416","country_code":"US","type":"funder","lineage":["https://openalex.org/I1321296531","https://openalex.org/I1343035065"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Raied Caromi","raw_affiliation_strings":["National Institute of Standards and Technology, Gaithersburg, MD, USA"],"raw_orcid":"https://orcid.org/0000-0002-8273-0642","affiliations":[{"raw_affiliation_string":"National Institute of Standards and Technology, Gaithersburg, MD, USA","institution_ids":["https://openalex.org/I1321296531"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5003918071"],"corresponding_institution_ids":["https://openalex.org/I1321296531"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":2.0257,"has_fulltext":true,"cited_by_count":16,"citation_normalized_percentile":{"value":0.86586129,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"11","issue":null,"first_page":"33498","last_page":"33508"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.9269000291824341,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.9269000291824341,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.02889999933540821,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.008299999870359898,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/path-loss","display_name":"Path loss","score":0.8123465776443481},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7918771505355835},{"id":"https://openalex.org/keywords/interference","display_name":"Interference (communication)","score":0.6451995968818665},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.580242395401001},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5570194721221924},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5327427983283997},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5164199471473694},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.48177358508110046},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.44097042083740234},{"id":"https://openalex.org/keywords/frequency-domain","display_name":"Frequency domain","score":0.438279390335083},{"id":"https://openalex.org/keywords/radio-spectrum","display_name":"Radio spectrum","score":0.43523871898651123},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.431551456451416},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.35971707105636597},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.21110251545906067},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.1491871476173401}],"concepts":[{"id":"https://openalex.org/C194273485","wikidata":"https://www.wikidata.org/wiki/Q1478845","display_name":"Path loss","level":3,"score":0.8123465776443481},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7918771505355835},{"id":"https://openalex.org/C32022120","wikidata":"https://www.wikidata.org/wiki/Q797225","display_name":"Interference (communication)","level":3,"score":0.6451995968818665},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.580242395401001},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5570194721221924},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5327427983283997},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5164199471473694},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.48177358508110046},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.44097042083740234},{"id":"https://openalex.org/C19118579","wikidata":"https://www.wikidata.org/wiki/Q786423","display_name":"Frequency domain","level":2,"score":0.438279390335083},{"id":"https://openalex.org/C92545706","wikidata":"https://www.wikidata.org/wiki/Q902174","display_name":"Radio spectrum","level":2,"score":0.43523871898651123},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.431551456451416},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.35971707105636597},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.21110251545906067},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.1491871476173401},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/access.2023.3264230","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3264230","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10091527.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmid:42040234","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42040234","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE access : practical innovations, open solutions","raw_type":null},{"id":"pmh:oai:doaj.org/article:5ccdce9787cd493a82efcca92a59b768","is_oa":true,"landing_page_url":"https://doaj.org/article/5ccdce9787cd493a82efcca92a59b768","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 11, Pp 33498-33508 (2023)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:13108494","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13108494/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.1109/access.2023.3264230","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2023.3264230","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/6514899/10091527.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8399999737739563,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320332176","display_name":"National Telecommunications and Information Administration","ror":"https://ror.org/04chq2495"},{"id":"https://openalex.org/F4320332178","display_name":"National Institute of Standards and Technology","ror":"https://ror.org/05xpvk416"},{"id":"https://openalex.org/F4320332538","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026"},{"id":"https://openalex.org/F4320337571","display_name":"Communications Technology Laboratory","ror":"https://ror.org/015xey021"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4362514623.pdf","grobid_xml":"https://content.openalex.org/works/W4362514623.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W1490921409","https://openalex.org/W1509061701","https://openalex.org/W2093540532","https://openalex.org/W2110002846","https://openalex.org/W2249053460","https://openalex.org/W2936660115","https://openalex.org/W2989258106","https://openalex.org/W3000408141","https://openalex.org/W3009345526","https://openalex.org/W3014079666","https://openalex.org/W3015635818","https://openalex.org/W3016523430","https://openalex.org/W3094656625","https://openalex.org/W3123855443","https://openalex.org/W3132288679","https://openalex.org/W3158432607","https://openalex.org/W3183937157","https://openalex.org/W3186604907","https://openalex.org/W3203643649","https://openalex.org/W4225107273","https://openalex.org/W4280570899","https://openalex.org/W4285058260"],"related_works":["https://openalex.org/W2497034207","https://openalex.org/W1949722210","https://openalex.org/W2153070213","https://openalex.org/W2537324052","https://openalex.org/W2889980946","https://openalex.org/W2146388675","https://openalex.org/W3119047119","https://openalex.org/W2532909097","https://openalex.org/W4225370042","https://openalex.org/W2791973964"],"abstract_inverted_index":{"In":[0],"the":[1,57,87,124,138],"6":[2,58],"GHz":[3,59],"spectrum":[4],"sharing":[5],"band,":[6,60],"unlicensed":[7],"devices":[8],"are":[9],"managed":[10],"by":[11],"automated":[12],"frequency":[13,55],"coordination":[14],"(AFC)":[15],"systems":[16],"to":[17,27,144],"protect":[18],"incumbent":[19],"services":[20],"from":[21,78,90],"interference.":[22],"Thus,":[23],"it":[24],"is":[25,68,100,149],"important":[26],"select":[28],"accurate":[29],"propagation":[30,109],"models":[31],"for":[32,45,94],"interference":[33],"calculation":[34],"and":[35,102,106],"analysis.":[36],"This":[37],"paper":[38],"utilizes":[39],"a":[40,53,69,79,91,129],"model-aided":[41],"deep":[42,125],"learning":[43,126],"technique":[44],"path":[46,95],"loss":[47,96],"prediction":[48,131],"at":[49],"7":[50],"GHz,":[51],"as":[52,84,86],"representative":[54],"within":[56],"in":[61,113,116],"an":[62,117],"urban":[63,118],"environment.":[64,119],"The":[65,98],"proposed":[66,141],"model":[67,83,99,127,142],"hybrid":[70],"model,":[71],"which":[72],"leverages":[73],"both":[74],"domain":[75],"expert":[76],"knowledge":[77],"physics-based":[80],"general-purposed":[81],"channel":[82],"well":[85],"learning-based":[88],"capability":[89],"neural":[92],"network,":[93],"prediction.":[97],"trained":[101],"tested":[103],"using":[104],"sufficient-quantity":[105],"high-quality":[107],"real":[108],"measurement":[110],"data":[111],"collected":[112],"four":[114],"locations":[115,146],"Numerical":[120],"results":[121],"show":[122],"that":[123],"provides":[128],"better":[130],"performance":[132],"than":[133],"most":[134],"empirical":[135],"models.":[136],"Furthermore,":[137],"feasibility":[139],"of":[140],"generalization":[143],"new":[145],"after":[147],"fine-tuning":[148],"examined.":[150]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}