{"id":"https://openalex.org/W4401857602","doi":"https://doi.org/10.1145/3637528.3671544","title":"Diffusion Model-based Mobile Traffic Generation with Open Data for Network Planning and Optimization","display_name":"Diffusion Model-based Mobile Traffic Generation with Open Data for Network Planning and Optimization","publication_year":2024,"publication_date":"2024-08-24","ids":{"openalex":"https://openalex.org/W4401857602","doi":"https://doi.org/10.1145/3637528.3671544"},"language":"en","primary_location":{"id":"doi:10.1145/3637528.3671544","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3637528.3671544","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3637528.3671544","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3637528.3671544","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037855353","display_name":"Haoye Chai","orcid":"https://orcid.org/0000-0002-6215-6671"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoye Chai","raw_affiliation_strings":["Department of Electronic Engineering, BNRist, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-6215-6671","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, BNRist, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047568691","display_name":"Tao Jiang","orcid":"https://orcid.org/0000-0002-1388-7478"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tao Jiang","raw_affiliation_strings":["Research Center of 6G Mobile Communications, School of Cyber Science and Engineering, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0002-1388-7478","affiliations":[{"raw_affiliation_string":"Research Center of 6G Mobile Communications, School of Cyber Science and Engineering, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053169627","display_name":"Li Yu","orcid":"https://orcid.org/0009-0006-2152-0234"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li Yu","raw_affiliation_strings":["Chinamobile Research Institute, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0006-2152-0234","affiliations":[{"raw_affiliation_string":"Chinamobile Research Institute, Beijing, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":13.0713,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.98887565,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"4828","last_page":"4838"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9929999709129333,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9632999897003174,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.751366376876831},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5777559280395508},{"id":"https://openalex.org/keywords/traffic-generation-model","display_name":"Traffic generation model","score":0.5685732364654541},{"id":"https://openalex.org/keywords/cellular-network","display_name":"Cellular network","score":0.49140655994415283},{"id":"https://openalex.org/keywords/network-planning-and-design","display_name":"Network planning and design","score":0.47720274329185486},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.43378493189811707},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.4018876850605011},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3747670352458954},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.31839534640312195},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.24459201097488403},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.12188482284545898}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.751366376876831},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5777559280395508},{"id":"https://openalex.org/C176715033","wikidata":"https://www.wikidata.org/wiki/Q2080768","display_name":"Traffic generation model","level":2,"score":0.5685732364654541},{"id":"https://openalex.org/C153646914","wikidata":"https://www.wikidata.org/wiki/Q535695","display_name":"Cellular network","level":2,"score":0.49140655994415283},{"id":"https://openalex.org/C114563136","wikidata":"https://www.wikidata.org/wiki/Q19725982","display_name":"Network planning and design","level":2,"score":0.47720274329185486},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.43378493189811707},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4018876850605011},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3747670352458954},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.31839534640312195},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.24459201097488403},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.12188482284545898}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3637528.3671544","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3637528.3671544","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3637528.3671544","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3637528.3671544","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3637528.3671544","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3637528.3671544","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.4300000071525574,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4401857602.pdf"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W2325027954","https://openalex.org/W2758725343","https://openalex.org/W2901701235","https://openalex.org/W2910883594","https://openalex.org/W2943457954","https://openalex.org/W2995790272","https://openalex.org/W3012303644","https://openalex.org/W3035524453","https://openalex.org/W3043558504","https://openalex.org/W3047312226","https://openalex.org/W3083822983","https://openalex.org/W3088157974","https://openalex.org/W3094402648","https://openalex.org/W3094605801","https://openalex.org/W3108316907","https://openalex.org/W3113921351","https://openalex.org/W3153325943","https://openalex.org/W3216866735","https://openalex.org/W4210623586","https://openalex.org/W4224317403","https://openalex.org/W4292259010","https://openalex.org/W4323042646","https://openalex.org/W4382316621","https://openalex.org/W4385562623","https://openalex.org/W4385955311","https://openalex.org/W4387846486","https://openalex.org/W4387846861","https://openalex.org/W4390100479"],"related_works":["https://openalex.org/W2114492868","https://openalex.org/W3085708078","https://openalex.org/W2132320513","https://openalex.org/W2538283180","https://openalex.org/W2063056766","https://openalex.org/W2068394611","https://openalex.org/W3013044429","https://openalex.org/W4285227736","https://openalex.org/W2794902412","https://openalex.org/W2074462449"],"abstract_inverted_index":{"With":[0],"the":[1,5,29,46,57,66,102,134,149,160,200,203,207,213],"rapid":[2],"development":[3],"of":[4,32,63,114,136,192,202,224],"Fifth":[6],"Generation":[7],"Mobile":[8,226],"Communication":[9],"Technology":[10],"(5G)":[11],"networks,":[12],"network":[13,23,30,39,43,137,153,216,221],"planning":[14,217],"and":[15,68,117,155,188,195],"optimization":[16,222],"have":[17],"become":[18],"increasingly":[19],"crucial.":[20],"Generating":[21],"high-fidelity":[22],"traffic":[24,86,138,154,209],"data":[25,47,210],"can":[26,131],"preemptively":[27],"estimate":[28],"demands":[31],"mobile":[33,85],"users,":[34],"which":[35,130],"holds":[36],"potential":[37],"for":[38,65,84,101],"operators":[40,214],"to":[41,56,97,147,211],"improve":[42],"performance.":[44],"However,":[45],"required":[48],"by":[49,186],"existing":[50,184],"generation":[51,87,135,163,193],"methods":[52,185],"is":[53,95,232],"predominantly":[54],"inaccessible":[55],"public,":[58],"resulting":[59],"in":[60,72,127,190],"a":[61,90,219],"lack":[62],"reproducibility":[64],"models":[67],"high":[69],"deployment":[70],"costs":[71],"practice.":[73],"In":[74],"this":[75],"article,":[76],"we":[77,205],"propose":[78],"an":[79,143],"Open":[80],"data-based":[81],"Diffusion":[82],"model":[83,104,182],"(OpenDiff),":[88],"where":[89,175],"multi-positive":[91],"contrastive":[92],"learning":[93],"algorithm":[94],"designed":[96],"construct":[98],"conditional":[99,121],"information":[100,122],"diffusion":[103],"using":[105],"entirely":[106],"publicly":[107],"available":[108,233],"satellite":[109],"remote":[110],"sensing":[111],"images,":[112],"Point":[113],"Interest":[115],"(POI),":[116],"population":[118],"data.":[119,139],"The":[120,229],"contains":[123],"relevant":[124],"human":[125,156],"activities":[126],"geographical":[128],"areas,":[129],"effectively":[132],"guide":[133],"We":[140,165],"further":[141,198],"design":[142],"attention-based":[144],"fusion":[145],"mechanism":[146],"capture":[148],"implicit":[150],"correlations":[151],"between":[152],"activity":[157],"features,":[158],"enhancing":[159],"model's":[161],"controllable":[162],"capability.":[164],"conduct":[166],"evaluations":[167],"on":[168,218],"three":[169],"different":[170],"cities":[171],"with":[172,215],"varying":[173],"scales,":[174],"experimental":[176],"results":[177],"verify":[178],"that":[179],"our":[180],"proposed":[181],"outperforms":[183],"14.36%":[187],"13.05%":[189],"terms":[191],"fidelity":[194],"controllability.":[196],"To":[197],"validate":[199],"effectiveness":[201],"model,":[204],"leverage":[206],"generated":[208],"assist":[212],"real-world":[220],"platform":[223],"China":[225],"Communications":[227],"Corporation.":[228],"source":[230],"code":[231],"online:https://github.com/impchai/OpenDiff-diffusion-model-with-open-data.":[234]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":8}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}