{"id":"https://openalex.org/W2750850773","doi":"https://doi.org/10.1109/tccn.2017.2746578","title":"Statistical Inference on Spectrum Data for Design and Enforcement of Harm Claim Thresholds","display_name":"Statistical Inference on Spectrum Data for Design and Enforcement of Harm Claim Thresholds","publication_year":2017,"publication_date":"2017-08-30","ids":{"openalex":"https://openalex.org/W2750850773","doi":"https://doi.org/10.1109/tccn.2017.2746578","mag":"2750850773"},"language":"en","primary_location":{"id":"doi:10.1109/tccn.2017.2746578","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tccn.2017.2746578","pdf_url":null,"source":{"id":"https://openalex.org/S2484188435","display_name":"IEEE Transactions on Cognitive Communications and Networking","issn_l":"2332-7731","issn":["2332-7731","2372-2045"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Cognitive Communications and Networking","raw_type":"journal-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/A5028886855","display_name":"Janne Riihij\u00e4rvi","orcid":"https://orcid.org/0000-0002-5989-3611"},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Janne Riihijarvi","raw_affiliation_strings":["Institute for Networked Systems, RWTH Aachen University, Aachen, Germany"],"raw_orcid":"https://orcid.org/0000-0002-5989-3611","affiliations":[{"raw_affiliation_string":"Institute for Networked Systems, RWTH Aachen University, Aachen, Germany","institution_ids":["https://openalex.org/I887968799"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031180041","display_name":"Petri M\u00e4h\u00f6nen","orcid":"https://orcid.org/0000-0001-6934-8636"},"institutions":[{"id":"https://openalex.org/I887968799","display_name":"RWTH Aachen University","ror":"https://ror.org/04xfq0f34","country_code":"DE","type":"education","lineage":["https://openalex.org/I887968799"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Petri Mahonen","raw_affiliation_strings":["Institute for Networked Systems, RWTH Aachen University, Aachen, Germany"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute for Networked Systems, RWTH Aachen University, Aachen, Germany","institution_ids":["https://openalex.org/I887968799"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066840153","display_name":"Jean Pierre De Vries","orcid":null},"institutions":[{"id":"https://openalex.org/I188538660","display_name":"University of Colorado Boulder","ror":"https://ror.org/02ttsq026","country_code":"US","type":"education","lineage":["https://openalex.org/I188538660"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"J. Pierre de Vries","raw_affiliation_strings":["Silicon Flatirons Center, University of Colorado, Boulder, CO, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Silicon Flatirons Center, University of Colorado, Boulder, CO, USA","institution_ids":["https://openalex.org/I188538660"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5028886855"],"corresponding_institution_ids":["https://openalex.org/I887968799"],"apc_list":null,"apc_paid":null,"fwci":0.1728,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.56682079,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"3","issue":"3","first_page":"520","last_page":"533"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9768000245094299,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},"topics":[{"id":"https://openalex.org/T11819","display_name":"Data-Driven Disease Surveillance","score":0.9768000245094299,"subfield":{"id":"https://openalex.org/subfields/2713","display_name":"Epidemiology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10391","display_name":"Healthcare Policy and Management","score":0.9753999710083008,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10243","display_name":"Statistical Methods and Bayesian Inference","score":0.973800003528595,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7980824708938599},{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.7559443116188049},{"id":"https://openalex.org/keywords/representativeness-heuristic","display_name":"Representativeness heuristic","score":0.6662663221359253},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5733299255371094},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.5585306286811829},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.48900306224823},{"id":"https://openalex.org/keywords/harm","display_name":"Harm","score":0.4618946313858032},{"id":"https://openalex.org/keywords/statistical-hypothesis-testing","display_name":"Statistical hypothesis testing","score":0.4578704833984375},{"id":"https://openalex.org/keywords/percentile","display_name":"Percentile","score":0.4531051814556122},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3505297303199768},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28850722312927246},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.1733514666557312}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7980824708938599},{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.7559443116188049},{"id":"https://openalex.org/C37381756","wikidata":"https://www.wikidata.org/wiki/Q20203288","display_name":"Representativeness heuristic","level":2,"score":0.6662663221359253},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5733299255371094},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.5585306286811829},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.48900306224823},{"id":"https://openalex.org/C2777363581","wikidata":"https://www.wikidata.org/wiki/Q15098235","display_name":"Harm","level":2,"score":0.4618946313858032},{"id":"https://openalex.org/C87007009","wikidata":"https://www.wikidata.org/wiki/Q210832","display_name":"Statistical hypothesis testing","level":2,"score":0.4578704833984375},{"id":"https://openalex.org/C122048520","wikidata":"https://www.wikidata.org/wiki/Q2913954","display_name":"Percentile","level":2,"score":0.4531051814556122},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3505297303199768},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28850722312927246},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.1733514666557312},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tccn.2017.2746578","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tccn.2017.2746578","pdf_url":null,"source":{"id":"https://openalex.org/S2484188435","display_name":"IEEE Transactions on Cognitive Communications and Networking","issn_l":"2332-7731","issn":["2332-7731","2372-2045"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Cognitive Communications and Networking","raw_type":"journal-article"},{"id":"pmh:oai:publications.rwth-aachen.de:711150","is_oa":false,"landing_page_url":"https://publications.rwth-aachen.de/record/711150","pdf_url":null,"source":{"id":"https://openalex.org/S4306401033","display_name":"RWTH Publications (RWTH Aachen)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I887968799","host_organization_name":"RWTH Aachen University","host_organization_lineage":["https://openalex.org/I887968799"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE transactions on cognitive communications and networking : TCCN 3(3), 520-533 (2017). doi:10.1109/TCCN.2017.2746578","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","score":0.6499999761581421,"id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W91922982","https://openalex.org/W1510709707","https://openalex.org/W1786463175","https://openalex.org/W2010135936","https://openalex.org/W2022000828","https://openalex.org/W2033080952","https://openalex.org/W2048209332","https://openalex.org/W2071181166","https://openalex.org/W2076427738","https://openalex.org/W2084801029","https://openalex.org/W2143022286","https://openalex.org/W2146846551","https://openalex.org/W2496675188","https://openalex.org/W2579190672","https://openalex.org/W2612682873","https://openalex.org/W3123701313","https://openalex.org/W4301028290","https://openalex.org/W6630563726"],"related_works":["https://openalex.org/W4211218949","https://openalex.org/W137830373","https://openalex.org/W2211820962","https://openalex.org/W3000984192","https://openalex.org/W3198676628","https://openalex.org/W1507171039","https://openalex.org/W2076107871","https://openalex.org/W2071142818","https://openalex.org/W191863844","https://openalex.org/W1976790773"],"abstract_inverted_index":{"Harm":[0],"claim":[1],"thresholds":[2,105],"(HCTs)":[3],"are":[4],"a":[5,15,19,56,114],"promising":[6],"approach":[7],"for":[8,60,67,162,192],"regulators":[9],"to":[10,27,118,126,159,174],"specify":[11],"interference":[12,31],"limits":[13],"in":[14,88,153],"technology-neutral":[16],"fashion,":[17],"and":[18,49,62,69,79,84,93,144],"useful":[20],"parameter":[21],"spectrum":[22],"access":[23],"systems":[24],"can":[25,171],"use":[26],"manage":[28],"the":[29,74,147,185,190],"aggregate":[30],"caused":[32],"by":[33],"transmitters":[34],"they":[35],"control.":[36],"However,":[37],"existing":[38,127],"literature":[39],"provides":[40],"very":[41],"little":[42],"guidance":[43],"how":[44,155,167],"HCTs":[45],"should":[46,116],"be":[47,160,172],"set":[48],"enforced.":[50],"In":[51],"this":[52],"paper,":[53],"we":[54,108],"propose":[55,109],"detailed":[57],"regulatory":[58],"framework":[59,136],"gathering":[61],"processing":[63],"of":[64,77,81,91,97,121,133,187],"measurement":[65,82],"data":[66,142,157,177],"enforcing":[68],"setting":[70],"HCTs.":[71],"We":[72,130,164],"introduce":[73],"central":[75],"concepts":[76],"stratification":[78],"weighting":[80],"data,":[83],"show":[85,145,166],"their":[86],"importance":[87],"ensuring":[89],"representativeness":[90,111],"measurements":[92],"enabling":[94],"robust":[95],"estimation":[96],"statistical":[98],"confidence":[99],"on":[100],"results.":[101],"For":[102],"deriving":[103],"HCT":[104,149],"from":[106],"measurements,":[107],"additional":[110],"criteria":[112],"that":[113,146,179],"regulator":[115],"apply":[117],"avoid":[119],"underestimation":[120],"field":[122],"strength":[123],"levels":[124],"related":[125],"wireless":[128],"services.":[129],"demonstrate":[131],"application":[132],"our":[134],"proposed":[135],"using":[137],"an":[138],"extensive":[139],"drive":[140],"test":[141],"set,":[143],"chosen":[148],"percentile":[150],"is":[151],"critical":[152],"determining":[154],"much":[156],"needs":[158],"gathered":[161],"enforcement.":[163],"also":[165],"spatial":[168],"prediction":[169],"techniques":[170],"used":[173],"deal":[175],"with":[176],"sets":[178],"have":[180],"been":[181],"collected":[182],"non-uniformly":[183],"over":[184],"region":[186],"interest,":[188],"emphasizing":[189],"need":[191],"modern":[193],"bias-corrected":[194],"techniques.":[195]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
