{"id":"https://openalex.org/W2413280466","doi":"https://doi.org/10.1109/lsp.2016.2577707","title":"Sparse Signal Detection for Space Shift Keying Using the Monte Carlo EM Algorithm","display_name":"Sparse Signal Detection for Space Shift Keying Using the Monte Carlo EM Algorithm","publication_year":2016,"publication_date":"2016-06-07","ids":{"openalex":"https://openalex.org/W2413280466","doi":"https://doi.org/10.1109/lsp.2016.2577707","mag":"2413280466"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2016.2577707","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2016.2577707","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","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/A5022303970","display_name":"Jinho Choi","orcid":"https://orcid.org/0000-0002-4895-6680"},"institutions":[{"id":"https://openalex.org/I39534123","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78","country_code":"KR","type":"education","lineage":["https://openalex.org/I39534123"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Jinho Choi","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology, Gwangju, South Korea","institution_ids":["https://openalex.org/I39534123"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5022303970"],"corresponding_institution_ids":["https://openalex.org/I39534123"],"apc_list":null,"apc_paid":null,"fwci":1.8511,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.83540901,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":"23","issue":"7","first_page":"974","last_page":"978"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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":0.9987000226974487,"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/T11458","display_name":"Advanced Wireless Communication 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"}}],"keywords":[{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.7729232311248779},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.6817929744720459},{"id":"https://openalex.org/keywords/matching-pursuit","display_name":"Matching pursuit","score":0.5766388177871704},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5709925889968872},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.5092836618423462},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.5043092966079712},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4841392934322357},{"id":"https://openalex.org/keywords/gibbs-sampling","display_name":"Gibbs sampling","score":0.4528426229953766},{"id":"https://openalex.org/keywords/keying","display_name":"Keying","score":0.45101597905158997},{"id":"https://openalex.org/keywords/detection-theory","display_name":"Detection theory","score":0.44333046674728394},{"id":"https://openalex.org/keywords/monte-carlo-algorithm","display_name":"Monte Carlo algorithm","score":0.42763644456863403},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.42636194825172424},{"id":"https://openalex.org/keywords/non-line-of-sight-propagation","display_name":"Non-line-of-sight propagation","score":0.41736841201782227},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.345079630613327},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.27547603845596313},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2445085048675537},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.1314975619316101},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.12243577837944031},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.12199276685714722},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11268457770347595}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.7729232311248779},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.6817929744720459},{"id":"https://openalex.org/C156872377","wikidata":"https://www.wikidata.org/wiki/Q6786281","display_name":"Matching pursuit","level":3,"score":0.5766388177871704},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5709925889968872},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.5092836618423462},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.5043092966079712},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4841392934322357},{"id":"https://openalex.org/C158424031","wikidata":"https://www.wikidata.org/wiki/Q1191905","display_name":"Gibbs sampling","level":3,"score":0.4528426229953766},{"id":"https://openalex.org/C2776542216","wikidata":"https://www.wikidata.org/wiki/Q6398306","display_name":"Keying","level":2,"score":0.45101597905158997},{"id":"https://openalex.org/C137270730","wikidata":"https://www.wikidata.org/wiki/Q120811","display_name":"Detection theory","level":3,"score":0.44333046674728394},{"id":"https://openalex.org/C15482360","wikidata":"https://www.wikidata.org/wiki/Q15238499","display_name":"Monte Carlo algorithm","level":3,"score":0.42763644456863403},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.42636194825172424},{"id":"https://openalex.org/C154910267","wikidata":"https://www.wikidata.org/wiki/Q1740982","display_name":"Non-line-of-sight propagation","level":3,"score":0.41736841201782227},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.345079630613327},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.27547603845596313},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2445085048675537},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.1314975619316101},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.12243577837944031},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.12199276685714722},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11268457770347595},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"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":2,"locations":[{"id":"doi:10.1109/lsp.2016.2577707","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2016.2577707","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"},{"id":"pmh:oai:dro.deakin.edu.au:DU:30118609","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306401102","display_name":"Own your potential (DEAKIN)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I149704539","host_organization_name":"Deakin University","host_organization_lineage":["https://openalex.org/I149704539"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal Article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321317","display_name":"Gwangju Institute of Science and Technology","ror":"https://ror.org/024kbgz78"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W143004564","https://openalex.org/W340244495","https://openalex.org/W1505940948","https://openalex.org/W1607198972","https://openalex.org/W1971733720","https://openalex.org/W1989009613","https://openalex.org/W2020999234","https://openalex.org/W2024266356","https://openalex.org/W2029262884","https://openalex.org/W2047834101","https://openalex.org/W2067605736","https://openalex.org/W2117853077","https://openalex.org/W2119667497","https://openalex.org/W2127271355","https://openalex.org/W2129131372","https://openalex.org/W2145096794","https://openalex.org/W2163504740","https://openalex.org/W2196956961","https://openalex.org/W2291051003","https://openalex.org/W2295559644","https://openalex.org/W2296616510","https://openalex.org/W3140968660","https://openalex.org/W4250955649","https://openalex.org/W4256217385","https://openalex.org/W4300263211"],"related_works":["https://openalex.org/W2172272784","https://openalex.org/W4307436769","https://openalex.org/W4323793210","https://openalex.org/W2366306259","https://openalex.org/W3101720559","https://openalex.org/W2143447014","https://openalex.org/W3172283447","https://openalex.org/W2110478555","https://openalex.org/W2109871577","https://openalex.org/W2353552312"],"abstract_inverted_index":{"In":[0],"order":[1],"to":[2,11,44,75],"detect":[3,76],"space":[4],"shift":[5],"keying":[6],"(SSK)":[7],"signals,":[8],"we":[9,25,39,51],"propose":[10],"use":[12],"the":[13,27,31,46,55,58,67],"Monte":[14],"Carlo":[15],"(MC)":[16],"expectation":[17],"maximization":[18],"(EM)":[19],"algorithm":[20,29,61],"in":[21],"this":[22],"paper.":[23],"First,":[24],"formulate":[26],"EM":[28],"for":[30],"maximum":[32],"likelihood":[33],"detection":[34],"of":[35,57,66],"SSK":[36,77],"signals.":[37],"Then,":[38],"derive":[40],"a":[41],"Gibbs":[42],"sampler":[43],"approximate":[45],"E-step.":[47],"Through":[48],"simulation":[49],"results,":[50],"can":[52],"see":[53],"that":[54,65],"performance":[56],"derived":[59],"MCEM":[60],"is":[62],"better":[63],"than":[64],"orthogonal":[68],"matching":[69],"pursuit":[70],"algorithm,":[71],"which":[72],"was":[73],"adopted":[74],"signals":[78],"with":[79],"low":[80],"complexity":[81],"by":[82],"Yu":[83],"et":[84],"al.":[85]},"counts_by_year":[{"year":2019,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}