{"id":"https://openalex.org/W3114102413","doi":"https://doi.org/10.1109/wcsp49889.2020.9299800","title":"Deep-learning-based Bouncing-order Prediction for Propagation Channel Characterization Using Graph Modeling","display_name":"Deep-learning-based Bouncing-order Prediction for Propagation Channel Characterization Using Graph Modeling","publication_year":2020,"publication_date":"2020-10-21","ids":{"openalex":"https://openalex.org/W3114102413","doi":"https://doi.org/10.1109/wcsp49889.2020.9299800","mag":"3114102413"},"language":"en","primary_location":{"id":"doi:10.1109/wcsp49889.2020.9299800","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcsp49889.2020.9299800","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Wireless Communications and Signal Processing (WCSP)","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/A5101717745","display_name":"Lin Yang","orcid":"https://orcid.org/0000-0002-9962-2787"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lin Yang","raw_affiliation_strings":["School of Electronics and Information Engineering, Tongji University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051230002","display_name":"Xuefeng Yin","orcid":"https://orcid.org/0000-0001-7216-8994"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuefeng Yin","raw_affiliation_strings":["National Computer and Information Technology Practical Education Demonstration Center, Tongji University, Shanghai, China","School of Electronics and Information Engineering, Tongji University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Computer and Information Technology Practical Education Demonstration Center, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]},{"raw_affiliation_string":"School of Electronics and Information Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069530484","display_name":"Jos\u00e9 Rodr\u00edguez-Pi\u00f1eiro","orcid":"https://orcid.org/0000-0002-7759-9619"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jose Rodriguez-Pineiro","raw_affiliation_strings":["School of Electronics and Information Engineering, Tongji University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Engineering, Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2081,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.53595085,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":95},"biblio":{"volume":"15","issue":null,"first_page":"998","last_page":"1002"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.9962999820709229,"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":0.9962999820709229,"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":0.9932000041007996,"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"}},{"id":"https://openalex.org/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9886999726295471,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.696631669998169},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.650362491607666},{"id":"https://openalex.org/keywords/fading","display_name":"Fading","score":0.6160718202590942},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.5579925179481506},{"id":"https://openalex.org/keywords/high-fidelity","display_name":"High fidelity","score":0.5265291929244995},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.504135251045227},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5010390281677246},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.4752870798110962},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.46997135877609253},{"id":"https://openalex.org/keywords/parametric-model","display_name":"Parametric model","score":0.4141024351119995},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36371222138404846},{"id":"https://openalex.org/keywords/acoustics","display_name":"Acoustics","score":0.21152958273887634},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17369449138641357},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.1702362596988678},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.13018009066581726},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1077909767627716}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.696631669998169},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.650362491607666},{"id":"https://openalex.org/C81978471","wikidata":"https://www.wikidata.org/wiki/Q1196572","display_name":"Fading","level":3,"score":0.6160718202590942},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.5579925179481506},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.5265291929244995},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.504135251045227},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5010390281677246},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.4752870798110962},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.46997135877609253},{"id":"https://openalex.org/C24574437","wikidata":"https://www.wikidata.org/wiki/Q7135228","display_name":"Parametric model","level":3,"score":0.4141024351119995},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36371222138404846},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.21152958273887634},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17369449138641357},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.1702362596988678},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.13018009066581726},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1077909767627716},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wcsp49889.2020.9299800","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcsp49889.2020.9299800","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on Wireless Communications and Signal Processing (WCSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1498436455","https://openalex.org/W1686810756","https://openalex.org/W1971443733","https://openalex.org/W2020108896","https://openalex.org/W2114420919","https://openalex.org/W2121733881","https://openalex.org/W2329494423","https://openalex.org/W2584943905","https://openalex.org/W2603396821","https://openalex.org/W2734408173","https://openalex.org/W2736068844","https://openalex.org/W2896510736","https://openalex.org/W2937796951","https://openalex.org/W2950473406","https://openalex.org/W2963408536","https://openalex.org/W2991270413","https://openalex.org/W6637373629","https://openalex.org/W6771201062"],"related_works":["https://openalex.org/W4313443006","https://openalex.org/W2289718384","https://openalex.org/W1995675544","https://openalex.org/W2945374968","https://openalex.org/W4385452045","https://openalex.org/W4293777179","https://openalex.org/W2164070813","https://openalex.org/W2135608140","https://openalex.org/W2895525995","https://openalex.org/W2509524819"],"abstract_inverted_index":{"The":[0,22,166],"propagation":[1,78,149],"of":[2,24,40,65,77,87,96,102,119,147,196],"electromagnetic":[3],"waves":[4,14],"can":[5,29,60,90,137,175,190],"be":[6,61,191],"traced":[7],"along":[8],"multiple":[9],"paths":[10],"where":[11],"interactions":[12],"between":[13],"and":[15,37,47,82,131,154],"objects":[16],"occur":[17],"resulting":[18],"in":[19],"\"bouncing\"":[20],"effect.":[21],"number":[23],"bounces,":[25],"called":[26],"as":[27,128],"\"bouncing-times\",":[28],"significantly":[30],"influence":[31],"the":[32,35,66,88,93,103,142,161,170,178,186],"fading":[33],"characteristics,":[34],"delay":[36,144],"angular":[38],"spreads":[39],"receiver":[41],"signals.":[42],"Therefore,":[43],"it":[44],"is":[45,55,70,122],"meaningful":[46],"valuable":[48],"to":[49,63,117,159,193],"research":[50],"on":[51,112],"bouncing-times.":[52],"Graph":[53],"modeling":[54,76,98],"an":[56,71],"efficient":[57],"technique":[58],"that":[59,136,169],"applied":[62,116],"simulation":[64],"channel":[67,198],"characteristics.":[68],"Bouncing-times":[69],"important":[72],"parameter":[73],"for":[74,180],"graph":[75,97],"characteristics":[79],"with":[80,99],"fidelity":[81],"accuracy.":[83],"A":[84],"proper":[85],"setting":[86],"bouncing-times":[89,120,139,179],"largely":[91],"reduce":[92],"computational":[94],"cost":[95],"no":[100],"tradeoff":[101],"performance.":[104],"In":[105],"this":[106],"work,":[107],"a":[108,133,148],"novel":[109],"method":[110,189],"based":[111],"deep":[113],"learning":[114],"(DL)":[115],"prediction":[118],"accurately":[121,176],"proposed.":[123],"We":[124],"choose":[125],"foliage":[126,181],"scenario":[127],"sample":[129],"environment":[130],"train":[132],"neural":[134,162,171],"network":[135,163,172],"predict":[138,177],"directly":[140],"from":[141],"power":[143],"profile":[145],"(PDP)":[146],"channel.":[150],"Both":[151],"experimental":[152],"PDPs":[153,156],"measurement":[155],"are":[157],"used":[158],"validate":[160],"being":[164,173],"trained.":[165],"result":[167],"shows":[168],"trained":[174],"scenario.":[182],"With":[183],"appropriate":[184],"modifications,":[185],"proposed":[187],"DL":[188],"generalized":[192],"more":[194],"scenarios":[195],"parametric":[197],"characterization.":[199]},"counts_by_year":[{"year":2021,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}