{"id":"https://openalex.org/W1567311658","doi":"https://doi.org/10.1109/spawc.2015.7227068","title":"Channel gain prediction in wireless networks based on spatial-temporal correlation","display_name":"Channel gain prediction in wireless networks based on spatial-temporal correlation","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W1567311658","doi":"https://doi.org/10.1109/spawc.2015.7227068","mag":"1567311658"},"language":"en","primary_location":{"id":"doi:10.1109/spawc.2015.7227068","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spawc.2015.7227068","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 16th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101645590","display_name":"Qi Liao","orcid":"https://orcid.org/0000-0001-7846-3812"},"institutions":[{"id":"https://openalex.org/I1322087612","display_name":"Alcatel Lucent (Germany)","ror":"https://ror.org/00c5mwp75","country_code":"DE","type":"company","lineage":["https://openalex.org/I1322087612"]},{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Qi Liao","raw_affiliation_strings":["Alcatel-Lucent, Bell Labs, Germany","Technische Universit\u00e4t Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Alcatel-Lucent, Bell Labs, Germany","institution_ids":["https://openalex.org/I1322087612"]},{"raw_affiliation_string":"Technische Universit\u00e4t Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105877821","display_name":"Stefan Valentin","orcid":"https://orcid.org/0000-0003-4181-402X"},"institutions":[{"id":"https://openalex.org/I1322087612","display_name":"Alcatel Lucent (Germany)","ror":"https://ror.org/00c5mwp75","country_code":"DE","type":"company","lineage":["https://openalex.org/I1322087612"]},{"id":"https://openalex.org/I4210123571","display_name":"Huawei Technologies (France)","ror":"https://ror.org/02rbzf697","country_code":"FR","type":"company","lineage":["https://openalex.org/I2250955327","https://openalex.org/I4210123571"]}],"countries":["DE","FR"],"is_corresponding":false,"raw_author_name":"Stefan Valentin","raw_affiliation_strings":["Alcatel-Lucent, Bell Labs, Germany","Huawei's Mathematical and Algorithmic Sciences Lab, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Alcatel-Lucent, Bell Labs, Germany","institution_ids":["https://openalex.org/I1322087612"]},{"raw_affiliation_string":"Huawei's Mathematical and Algorithmic Sciences Lab, France","institution_ids":["https://openalex.org/I4210123571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068274314","display_name":"S\u0142awomir Sta\u0144czak","orcid":"https://orcid.org/0000-0003-3829-4668"},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Slawomir Stanczak","raw_affiliation_strings":["Technische Universit\u00e4t Berlin, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technische Universit\u00e4t Berlin, Germany","institution_ids":["https://openalex.org/I4577782"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":17,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"400","last_page":"404"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9994000196456909,"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":0.9994000196456909,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9984999895095825,"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/T10575","display_name":"Wireless Communication Networks Research","score":0.9962000250816345,"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/autoregressive-model","display_name":"Autoregressive model","score":0.8499144911766052},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7860440611839294},{"id":"https://openalex.org/keywords/spatial-correlation","display_name":"Spatial correlation","score":0.6379645466804504},{"id":"https://openalex.org/keywords/fading","display_name":"Fading","score":0.5307355523109436},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.5260916948318481},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.4924963414669037},{"id":"https://openalex.org/keywords/rayleigh-fading","display_name":"Rayleigh fading","score":0.48079434037208557},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.4732906222343445},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4649715721607208},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.4514245092868805},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3850753903388977},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.37475764751434326},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.34166210889816284},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33931005001068115},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.31513530015945435},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.16823720932006836},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1493876874446869},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10388576984405518}],"concepts":[{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.8499144911766052},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7860440611839294},{"id":"https://openalex.org/C150060386","wikidata":"https://www.wikidata.org/wiki/Q7574054","display_name":"Spatial correlation","level":2,"score":0.6379645466804504},{"id":"https://openalex.org/C81978471","wikidata":"https://www.wikidata.org/wiki/Q1196572","display_name":"Fading","level":3,"score":0.5307355523109436},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.5260916948318481},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4924963414669037},{"id":"https://openalex.org/C56985126","wikidata":"https://www.wikidata.org/wiki/Q854039","display_name":"Rayleigh fading","level":4,"score":0.48079434037208557},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.4732906222343445},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4649715721607208},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4514245092868805},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3850753903388977},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.37475764751434326},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34166210889816284},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33931005001068115},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.31513530015945435},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.16823720932006836},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1493876874446869},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10388576984405518},{"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/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/spawc.2015.7227068","is_oa":false,"landing_page_url":"https://doi.org/10.1109/spawc.2015.7227068","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 16th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)","raw_type":"proceedings-article"},{"id":"pmh:oai:fraunhofer.de:N-589538","is_oa":false,"landing_page_url":"http://publica.fraunhofer.de/documents/N-589538.html","pdf_url":null,"source":{"id":"https://openalex.org/S4306400801","display_name":"Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Fraunhofer HHI","raw_type":"Conference Paper"},{"id":"pmh:oai:publica.fraunhofer.de:publica/407844","is_oa":false,"landing_page_url":"https://publica.fraunhofer.de/handle/publica/407844","pdf_url":null,"source":{"id":"https://openalex.org/S4306400318","display_name":"Fraunhofer-Publica (Fraunhofer-Gesellschaft)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4923324","host_organization_name":"Fraunhofer-Gesellschaft","host_organization_lineage":["https://openalex.org/I4923324"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"conference paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W24067677","https://openalex.org/W1549390603","https://openalex.org/W1607198972","https://openalex.org/W1820976938","https://openalex.org/W1980032585","https://openalex.org/W1986280275","https://openalex.org/W2033685429","https://openalex.org/W2039216363","https://openalex.org/W2117206394","https://openalex.org/W2148180395","https://openalex.org/W2149684933","https://openalex.org/W2157293015","https://openalex.org/W2162266217","https://openalex.org/W3106096591","https://openalex.org/W3140968660","https://openalex.org/W4250212474","https://openalex.org/W6600981286"],"related_works":["https://openalex.org/W2116044594","https://openalex.org/W2101999641","https://openalex.org/W1503152075","https://openalex.org/W301676527","https://openalex.org/W2052600062","https://openalex.org/W2124541664","https://openalex.org/W289296924","https://openalex.org/W2076148615","https://openalex.org/W2122920812","https://openalex.org/W2109988226"],"abstract_inverted_index":{"Due":[0],"to":[1,27,62],"the":[2,7,29,77],"popularity":[3],"of":[4,9,32,56,65,68],"GPS-enabled":[5],"Smartphones":[6],"location":[8,20],"mobile":[10,33],"terminals":[11],"has":[12],"become":[13],"widely":[14],"available":[15],"[1].":[16],"Aided":[17],"by":[18],"such":[19],"information,":[21],"we":[22],"propose":[23],"a":[24,49,69],"general":[25],"model":[26,42],"predict":[28],"channel":[30],"gain":[31],"users":[34],"for":[35,88],"multiple":[36],"time":[37],"steps":[38],"in":[39,48],"advance.":[40],"Our":[41],"exploits":[43],"spatial":[44],"and":[45,91],"temporal":[46],"correlation":[47],"Bayesian":[50],"framework.":[51],"The":[52],"framework":[53],"is":[54,93],"composed":[55],"an":[57],"autoregressive":[58],"process":[59],"and,":[60],"according":[61],"our":[63],"analysis":[64],"Rayleigh":[66],"fading,":[67],"multivariate":[70],"Gaussian":[71],"process.":[72],"Numerical":[73],"results":[74],"shows":[75],"that":[76],"proposed":[78],"algorithm":[79],"(i)":[80],"achieves":[81],"much":[82],"higher":[83],"accuracy":[84],"than":[85,97],"autoregression,":[86],"especially":[87],"long-term":[89],"prediction,":[90],"(ii)":[92],"substantially":[94],"more":[95],"robust":[96],"support":[98],"vector":[99],"machines":[100],"against":[101],"localization":[102],"errors.":[103]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":3},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
