{"id":"https://openalex.org/W2908252754","doi":"https://doi.org/10.1109/pimrc.2018.8580992","title":"Propagation-model-free Coverage Evaluation via Machine Learning for Future 5G Networks","display_name":"Propagation-model-free Coverage Evaluation via Machine Learning for Future 5G Networks","publication_year":2018,"publication_date":"2018-09-01","ids":{"openalex":"https://openalex.org/W2908252754","doi":"https://doi.org/10.1109/pimrc.2018.8580992","mag":"2908252754"},"language":"en","primary_location":{"id":"doi:10.1109/pimrc.2018.8580992","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pimrc.2018.8580992","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","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/A5007276418","display_name":"Lingcheng Dai","orcid":"https://orcid.org/0000-0001-7627-6343"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lingcheng Dai","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100400403","display_name":"Hongtao Zhang","orcid":"https://orcid.org/0000-0003-2031-5985"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongtao Zhang","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037777681","display_name":"Yanli Zhuang","orcid":"https://orcid.org/0000-0003-4700-5207"},"institutions":[{"id":"https://openalex.org/I4210160618","display_name":"Huawei Technologies (United Kingdom)","ror":"https://ror.org/056gzgs71","country_code":"GB","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210160618"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Yanli Zhuang","raw_affiliation_strings":["Huawei Technologies Co. Ltd"],"affiliations":[{"raw_affiliation_string":"Huawei Technologies Co. Ltd","institution_ids":["https://openalex.org/I4210160618"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5007276418"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.913,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":{"value":0.77276064,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9997000098228455,"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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9997000098228455,"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/T10936","display_name":"Millimeter-Wave Propagation and Modeling","score":0.9997000098228455,"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":0.996999979019165,"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":0.8173272609710693},{"id":"https://openalex.org/keywords/rss","display_name":"RSS","score":0.7181233763694763},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.7009000182151794},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6402225494384766},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.6159968972206116},{"id":"https://openalex.org/keywords/hyperparameter-optimization","display_name":"Hyperparameter optimization","score":0.5933329463005066},{"id":"https://openalex.org/keywords/software-deployment","display_name":"Software deployment","score":0.5516687631607056},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5458082556724548},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.4930064380168915},{"id":"https://openalex.org/keywords/signal-strength","display_name":"Signal strength","score":0.46627309918403625},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.438036173582077},{"id":"https://openalex.org/keywords/base-station","display_name":"Base station","score":0.4336298704147339},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.1640506088733673},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10332423448562622}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8173272609710693},{"id":"https://openalex.org/C2385561","wikidata":"https://www.wikidata.org/wiki/Q45432","display_name":"RSS","level":2,"score":0.7181233763694763},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.7009000182151794},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6402225494384766},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6159968972206116},{"id":"https://openalex.org/C10485038","wikidata":"https://www.wikidata.org/wiki/Q48996162","display_name":"Hyperparameter optimization","level":3,"score":0.5933329463005066},{"id":"https://openalex.org/C105339364","wikidata":"https://www.wikidata.org/wiki/Q2297740","display_name":"Software deployment","level":2,"score":0.5516687631607056},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5458082556724548},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.4930064380168915},{"id":"https://openalex.org/C176808163","wikidata":"https://www.wikidata.org/wiki/Q17105794","display_name":"Signal strength","level":3,"score":0.46627309918403625},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.438036173582077},{"id":"https://openalex.org/C68649174","wikidata":"https://www.wikidata.org/wiki/Q1379116","display_name":"Base station","level":2,"score":0.4336298704147339},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.1640506088733673},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10332423448562622},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"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":"doi:10.1109/pimrc.2018.8580992","is_oa":false,"landing_page_url":"https://doi.org/10.1109/pimrc.2018.8580992","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 29th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","score":0.6499999761581421,"id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W2097998348","https://openalex.org/W2101234009","https://openalex.org/W2103633133","https://openalex.org/W2398409936","https://openalex.org/W2507855797","https://openalex.org/W2508019862","https://openalex.org/W2562326633","https://openalex.org/W2568548648","https://openalex.org/W2783993409","https://openalex.org/W6675354045","https://openalex.org/W6676047094","https://openalex.org/W6747819531"],"related_works":["https://openalex.org/W2162859609","https://openalex.org/W4200318234","https://openalex.org/W2022445516","https://openalex.org/W150547863","https://openalex.org/W1891938465","https://openalex.org/W1550605711","https://openalex.org/W2982532306","https://openalex.org/W1639914594","https://openalex.org/W4237766728","https://openalex.org/W2089197460"],"abstract_inverted_index":{"As":[0],"densification":[1],"and":[2,31,66,77,84,167],"heterogeneity":[3],"are":[4,82,143],"the":[5,22,70,94,97,103,115,158,168],"promising":[6],"trends":[7],"of":[8,13,25,80,162,182],"future":[9],"mobile":[10],"networks,":[11],"deployment":[12],"base":[14],"stations":[15],"(BSs)":[16],"becomes":[17],"increasingly":[18],"difficult":[19],"due":[20],"to":[21,86,92,106,124,188],"laborious":[23],"procedures":[24,105],"alternating":[26],"optimization":[27,130],"between":[28],"field":[29],"measurements":[30],"coverage":[32,43,119],"evaluation":[33,44],"via":[34,133],"propagation":[35,55,108],"models.":[36],"In":[37,57,100],"this":[38,101],"paper,":[39],"we":[40],"present":[41],"a":[42,88,151],"tool":[45],"based":[46],"on":[47],"machine":[48,164],"learning":[49,140,165],"(ML)":[50],"which":[51,90,113,185],"is":[52,131,186],"free":[53],"from":[54],"model.":[56],"particular,":[58],"received":[59],"signal":[60],"strengths":[61],"(RSSs)":[62],"reported":[63],"by":[64,145,160],"users":[65],"factors":[67],"that":[68,172],"affect":[69],"transmitted":[71],"signal,":[72],"such":[73],"as":[74],"distance,":[75],"geography":[76],"configuration":[78],"parameters":[79],"BS,":[81],"collected":[83],"used":[85],"train":[87],"classifier":[89],"allows":[91],"predict":[93],"RSS":[95],"at":[96],"user":[98],"side.":[99],"way,":[102],"complicated":[104],"obtain":[107],"model":[109],"can":[110],"be":[111],"skipped,":[112],"reduces":[114],"great":[116],"cost":[117],"in":[118,122,138,180],"evaluation.":[120],"Moreover,":[121],"order":[123],"acquire":[125],"better":[126,152],"prediction":[127,183],"performance,":[128],"hyper-parameters":[129],"performed":[132],"exhaustive":[134],"grid":[135],"search":[136],"methods":[137],"each":[139],"algorithm.":[141],"Simulations":[142],"conducted":[144],"using":[146],"vast":[147],"real-world":[148],"data":[149],"for":[150],"training":[153],"result.":[154],"We":[155],"also":[156],"compare":[157],"performance":[159],"means":[161],"different":[163],"algorithms":[166],"numerical":[169],"results":[170],"show":[171],"Support":[173],"Vector":[174],"Machine":[175],"(SVM)":[176],"outperforms":[177],"other":[178],"classifiers":[179],"terms":[181],"accuracy,":[184],"up":[187],"86.7%.":[189]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}
