{"id":"https://openalex.org/W4304589862","doi":"https://doi.org/10.1109/ghtc55712.2022.9911009","title":"Deep Learning-Based Path Loss Prediction Model for 5G mmWave","display_name":"Deep Learning-Based Path Loss Prediction Model for 5G mmWave","publication_year":2022,"publication_date":"2022-09-08","ids":{"openalex":"https://openalex.org/W4304589862","doi":"https://doi.org/10.1109/ghtc55712.2022.9911009"},"language":"en","primary_location":{"id":"doi:10.1109/ghtc55712.2022.9911009","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ghtc55712.2022.9911009","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Global Humanitarian Technology Conference (GHTC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073095436","display_name":"Simon Karanja Hinga","orcid":"https://orcid.org/0000-0002-5827-3525"},"institutions":[{"id":"https://openalex.org/I16269868","display_name":"Santa Clara University","ror":"https://ror.org/03ypqe447","country_code":"US","type":"education","lineage":["https://openalex.org/I16269868"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Simon K. Hinga","raw_affiliation_strings":["Santa Clara University,Department of Electrical and Computer Engineering,California,USA","Department of Electrical and Computer Engineering, Santa Clara University, California, USA"],"affiliations":[{"raw_affiliation_string":"Santa Clara University,Department of Electrical and Computer Engineering,California,USA","institution_ids":["https://openalex.org/I16269868"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Santa Clara University, California, USA","institution_ids":["https://openalex.org/I16269868"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047701388","display_name":"Oluwaseun T. Ajayi","orcid":"https://orcid.org/0000-0001-8659-6199"},"institutions":[{"id":"https://openalex.org/I180949307","display_name":"Illinois Institute of Technology","ror":"https://ror.org/037t3ry66","country_code":"US","type":"education","lineage":["https://openalex.org/I180949307"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Oluwaseun T. Ajayi","raw_affiliation_strings":["Illinois Institute of Technology,Department of Electrical and Computer Engineering,Chicago,USA","Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, USA"],"affiliations":[{"raw_affiliation_string":"Illinois Institute of Technology,Department of Electrical and Computer Engineering,Chicago,USA","institution_ids":["https://openalex.org/I180949307"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Illinois Institute of Technology, Chicago, USA","institution_ids":["https://openalex.org/I180949307"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025538938","display_name":"Tokunbo Ogunfunmi","orcid":"https://orcid.org/0000-0003-3517-9779"},"institutions":[{"id":"https://openalex.org/I16269868","display_name":"Santa Clara University","ror":"https://ror.org/03ypqe447","country_code":"US","type":"education","lineage":["https://openalex.org/I16269868"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tokunbo Ogunfunmi","raw_affiliation_strings":["Santa Clara University,Department of Electrical and Computer Engineering,California,USA","Department of Electrical and Computer Engineering, Santa Clara University, California, USA"],"affiliations":[{"raw_affiliation_string":"Santa Clara University,Department of Electrical and Computer Engineering,California,USA","institution_ids":["https://openalex.org/I16269868"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Santa Clara University, California, USA","institution_ids":["https://openalex.org/I16269868"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5073095436"],"corresponding_institution_ids":["https://openalex.org/I16269868"],"apc_list":null,"apc_paid":null,"fwci":0.7388,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.69352192,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"114","last_page":"120"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9995999932289124,"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/T13905","display_name":"Telecommunications and Broadcasting Technologies","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8136024475097656},{"id":"https://openalex.org/keywords/path-loss","display_name":"Path loss","score":0.7236076593399048},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6213676929473877},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.5589329600334167},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5551999807357788},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5274857878684998},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.5210201740264893},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5125803351402283},{"id":"https://openalex.org/keywords/wireless-network","display_name":"Wireless network","score":0.4853155016899109},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4542567729949951},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.2164246141910553},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.140828937292099}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8136024475097656},{"id":"https://openalex.org/C194273485","wikidata":"https://www.wikidata.org/wiki/Q1478845","display_name":"Path loss","level":3,"score":0.7236076593399048},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6213676929473877},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.5589329600334167},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5551999807357788},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5274857878684998},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.5210201740264893},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5125803351402283},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.4853155016899109},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4542567729949951},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2164246141910553},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.140828937292099}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ghtc55712.2022.9911009","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ghtc55712.2022.9911009","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE Global Humanitarian Technology Conference (GHTC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320311294","display_name":"Santa Clara University","ror":"https://ror.org/03ypqe447"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1995813985","https://openalex.org/W2020108896","https://openalex.org/W2061052237","https://openalex.org/W2090380102","https://openalex.org/W2091005538","https://openalex.org/W2093540532","https://openalex.org/W2118720406","https://openalex.org/W2167771090","https://openalex.org/W2219770862","https://openalex.org/W2248726416","https://openalex.org/W2512795728","https://openalex.org/W2551388604","https://openalex.org/W2771579582","https://openalex.org/W2923764929","https://openalex.org/W2955338161","https://openalex.org/W2963634393","https://openalex.org/W3000408141","https://openalex.org/W3019397672","https://openalex.org/W3036330215","https://openalex.org/W3038758042","https://openalex.org/W3041437500","https://openalex.org/W3106204509","https://openalex.org/W3106736415","https://openalex.org/W3123882998","https://openalex.org/W3202342854","https://openalex.org/W4224282094","https://openalex.org/W4255941384"],"related_works":["https://openalex.org/W1588057903","https://openalex.org/W4375867731","https://openalex.org/W2953613577","https://openalex.org/W1949722210","https://openalex.org/W1973901544","https://openalex.org/W2158685349","https://openalex.org/W4281388183","https://openalex.org/W3121470477","https://openalex.org/W2803573071","https://openalex.org/W2947593622"],"abstract_inverted_index":{"The":[0,33],"proliferation":[1],"of":[2,35,65,88,112],"wireless":[3],"devices":[4],"that":[5,99],"utilize":[6],"the":[7,22,54,63,104,110],"5G":[8,94,113],"mmWave":[9],"technology":[10],"continues":[11],"to":[12,52,84],"stir":[13],"several":[14],"design":[15,64],"requirements":[16],"for":[17],"optimizing":[18],"performance.":[19],"However,":[20],"mitigating":[21],"underlying":[23],"constraints":[24],"posed":[25],"by":[26],"path":[27,57,89,105],"loss":[28,58,90,106],"remains":[29],"a":[30,48,66,70,92],"challenging":[31],"task.":[32],"use":[34],"empirical":[36],"methods":[37],"and":[38,69,80],"heuristic":[39],"techniques":[40],"have":[41],"only":[42],"provided":[43],"one-shot":[44],"solution.":[45],"We":[46,97],"adopt":[47],"reusable":[49],"learning-based":[50],"method":[51,61],"alleviate":[53,103],"complexity":[55,108],"in":[56,91,109],"prediction.":[59],"Our":[60],"involves":[62],"deep":[67,100],"classifier":[68],"regression":[71],"model":[72],"which":[73],"learn":[74],"relevant":[75],"network":[76],"parameters":[77],"from":[78],"data":[79],"uses":[81],"such":[82],"knowledge":[83],"differentiate":[85],"different":[86],"classes":[87],"practical":[93],"radio":[95],"environment.":[96],"show":[98],"learning":[101],"can":[102],"modelling":[107],"optimization":[111],"networks.":[114]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":6}],"updated_date":"2026-04-04T08:04:53.788161","created_date":"2025-10-10T00:00:00"}