{"id":"https://openalex.org/W3034530297","doi":null,"title":"Deep learning approaches for fast radio signal prediction.","display_name":"Deep learning approaches for fast radio signal prediction.","publication_year":2020,"publication_date":"2020-06-16","ids":{"openalex":"https://openalex.org/W3034530297","mag":"3034530297"},"language":"en","primary_location":{"id":"mag:3034530297","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2006.09245","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://export.arxiv.org/pdf/2006.09245","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5064988998","display_name":"Ozan Ozyegen","orcid":"https://orcid.org/0000-0002-7493-8056","observed_orcids":["https://orcid.org/0000-0002-7493-8056"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ozan Ozyegen","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-7493-8056","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002433008","display_name":"Sanaz Mohammadjafari","orcid":"https://orcid.org/0000-0003-0820-9477","observed_orcids":["https://orcid.org/0000-0003-0820-9477"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sanaz Mohammadjafari","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-0820-9477","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036720349","display_name":"Karim El Mokhtari","orcid":"https://orcid.org/0000-0002-0204-1119","observed_orcids":["https://orcid.org/0000-0002-0204-1119"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Karim El Mokhtari","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0002-0204-1119","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070091996","display_name":"M\u00fccahit \u00c7evik","orcid":"https://orcid.org/0000-0003-4020-6305","observed_orcids":["https://orcid.org/0000-0003-4020-6305"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"M\u00fccahit \u00c7evik","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-4020-6305","affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060014929","display_name":"Jonathan Ethier","orcid":"https://orcid.org/0000-0003-2377-6496","observed_orcids":["https://orcid.org/0000-0003-2377-6496"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jonathan Ethier","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-2377-6496","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5080569424","display_name":"Ay\u015fe Bener","orcid":"https://orcid.org/0000-0003-4934-8326","observed_orcids":["https://orcid.org/0000-0003-4934-8326"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ay\u015fe Bener","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-4934-8326","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.9955999851226807,"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":0.9955999851226807,"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/T11409","display_name":"Advanced Wireless Network Optimization","score":0.0003000000142492354,"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/T10579","display_name":"Cognitive Radio Networks and Spectrum Sensing","score":0.00019999999494757503,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/dense-urban-areas","display_name":"dense urban areas","score":0.7379999756813049},{"id":"https://openalex.org/keywords/deep-neural-network","display_name":"deep neural network","score":0.777999997138977},{"id":"https://openalex.org/keywords/u-net","display_name":"U-Net","score":0.8119999766349792},{"id":"https://openalex.org/keywords/ray-tracing","display_name":"ray tracing","score":0.7670000195503235},{"id":"https://openalex.org/keywords/building-shape","display_name":"building geometry","score":0.4650000035762787},{"id":"https://openalex.org/keywords/radio-wave-propagation","display_name":"radio wave propagation","score":0.6629999876022339},{"id":"https://openalex.org/keywords/strided-convolution","display_name":"strided convolution","score":0.7300000190734863},{"id":"https://openalex.org/keywords/inception-module","display_name":"Inception module","score":0.9929999709129333}],"concepts":[{"id":"https://openalex.org/C47798520","wikidata":"https://www.wikidata.org/wiki/Q190157","display_name":"Transmitter","level":3,"score":0.881180465221405},{"id":"https://openalex.org/C121483023","wikidata":"https://www.wikidata.org/wiki/Q7298343","display_name":"Ray tracing (physics)","level":2,"score":0.8312211036682129},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.743556022644043},{"id":"https://openalex.org/C138673069","wikidata":"https://www.wikidata.org/wiki/Q322229","display_name":"Tracing","level":2,"score":0.6525534987449646},{"id":"https://openalex.org/C202311505","wikidata":"https://www.wikidata.org/wiki/Q1474701","display_name":"Radio propagation","level":2,"score":0.5983862280845642},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5130339860916138},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4896557927131653},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.4634864628314972},{"id":"https://openalex.org/C82744980","wikidata":"https://www.wikidata.org/wiki/Q951513","display_name":"Distributed ray tracing","level":3,"score":0.4566260576248169},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3870014548301697},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.33626019954681396},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.2584676444530487},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12677189707756042},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.07518142461776733},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07448238134384155},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"mag:3034530297","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2006.09245","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null}],"best_oa_location":{"id":"mag:3034530297","doi":null,"is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2006.09245","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.5378999710083008,"display_name":"Industry, innovation and infrastructure"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W2167510172","https://openalex.org/W2194775991","https://openalex.org/W2432481613","https://openalex.org/W2517954747","https://openalex.org/W2559597482"],"related_works":["https://openalex.org/W3200813303","https://openalex.org/W4313033894","https://openalex.org/W4395666960","https://openalex.org/W2990694113","https://openalex.org/W7202254662","https://openalex.org/W3162011346","https://openalex.org/W4312355809","https://openalex.org/W3009345526","https://openalex.org/W4281570319","https://openalex.org/W3097713188"],"abstract_inverted_index":{"The":[0,79],"aim":[1],"of":[2,8,41],"this":[3],"work":[4],"is":[5,23],"the":[6,26,36,39,70,97,111,118],"prediction":[7],"power":[9,71],"coverage":[10,72],"in":[11,35,38],"a":[12],"dense":[13],"urban":[14],"environment":[15],"given":[16],"building":[17],"and":[18,52,68,76,86,116],"transmitter":[19,77,113],"locations.":[20],"Conventionally":[21],"ray-tracing":[22,47,66,98],"regarded":[24],"as":[25],"most":[27],"accurate":[28,91],"method":[29],"to":[30,63,96,108],"predict":[31,69],"energy":[32],"distribution":[33],"patterns":[34],"area":[37],"presence":[40],"diverse":[42],"radio":[43],"propagation":[44],"phenomena.":[45],"However,":[46],"simulations":[48],"are":[49,94],"time":[50,120],"consuming":[51],"require":[53],"extensive":[54],"computational":[55],"resources.":[56],"We":[57],"propose":[58],"deep":[59],"neural":[60],"network":[61],"models":[62],"learn":[64],"from":[65,74],"results":[67,92],"dynamically":[73],"buildings":[75],"properties.":[78],"proposed":[80],"UNET":[81],"model":[82,104],"with":[83],"strided":[84],"convolutions":[85],"inception":[87],"modules":[88],"provide":[89],"highly":[90],"that":[93],"close":[95],"output":[99],"on":[100],"32x32":[101],"frames.":[102],"This":[103],"will":[105],"allow":[106],"practitioners":[107],"search":[109],"for":[110],"best":[112],"locations":[114],"effectively":[115],"reduce":[117],"design":[119],"significantly.":[121]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-09-26T08:19:03.415552","created_date":"2020-06-19T00:00:00"}
