{"id":"https://openalex.org/W2463999977","doi":"https://doi.org/10.1109/vtcspring.2016.7504144","title":"Bayesian Block-Sparse Channel Estimation for Large-Scale MISO-OFDM Systems","display_name":"Bayesian Block-Sparse Channel Estimation for Large-Scale MISO-OFDM Systems","publication_year":2016,"publication_date":"2016-05-01","ids":{"openalex":"https://openalex.org/W2463999977","doi":"https://doi.org/10.1109/vtcspring.2016.7504144","mag":"2463999977"},"language":"en","primary_location":{"id":"doi:10.1109/vtcspring.2016.7504144","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtcspring.2016.7504144","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 83rd Vehicular Technology Conference (VTC Spring)","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/A5101610424","display_name":"Hailin Li","orcid":"https://orcid.org/0000-0003-4339-6108"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hailin Li","raw_affiliation_strings":["Department of Information Communication Engineering, Xi'an Jiaotong University, Xi'an, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Communication Engineering, Xi'an Jiaotong University, Xi'an, P. R. China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072183477","display_name":"Feng Li","orcid":"https://orcid.org/0000-0001-6957-5388"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Li","raw_affiliation_strings":["Department of Information Communication Engineering, Xi'an Jiaotong University, Xi'an, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Communication Engineering, Xi'an Jiaotong University, Xi'an, P. R. China","institution_ids":["https://openalex.org/I87445476"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100647301","display_name":"Shuyuan Li","orcid":"https://orcid.org/0000-0001-7428-3988"},"institutions":[{"id":"https://openalex.org/I87445476","display_name":"Xi'an Jiaotong University","ror":"https://ror.org/017zhmm22","country_code":"CN","type":"education","lineage":["https://openalex.org/I87445476"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuyuan Li","raw_affiliation_strings":["Department of Information Communication Engineering, Xi'an Jiaotong University, Xi'an, P. R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Information Communication Engineering, Xi'an Jiaotong University, Xi'an, P. R. China","institution_ids":["https://openalex.org/I87445476"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I87445476"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"1","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":0.9994000196456909,"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/T10125","display_name":"Advanced Wireless Communication Techniques","score":0.9993000030517578,"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/T10931","display_name":"Direction-of-Arrival Estimation Techniques","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/orthogonal-frequency-division-multiplexing","display_name":"Orthogonal frequency-division multiplexing","score":0.69783616065979},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.6400039196014404},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6262083053588867},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5950702428817749},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.5937656760215759},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5921595096588135},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5524576306343079},{"id":"https://openalex.org/keywords/impulse","display_name":"Impulse (physics)","score":0.45272165536880493},{"id":"https://openalex.org/keywords/multiplexing","display_name":"Multiplexing","score":0.4444272518157959},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.4376087486743927},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.434885710477829},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.31527259945869446},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2980732023715973},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.1494598090648651}],"concepts":[{"id":"https://openalex.org/C40409654","wikidata":"https://www.wikidata.org/wiki/Q375889","display_name":"Orthogonal frequency-division multiplexing","level":3,"score":0.69783616065979},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.6400039196014404},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6262083053588867},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5950702428817749},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.5937656760215759},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5921595096588135},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5524576306343079},{"id":"https://openalex.org/C70836080","wikidata":"https://www.wikidata.org/wiki/Q837940","display_name":"Impulse (physics)","level":2,"score":0.45272165536880493},{"id":"https://openalex.org/C19275194","wikidata":"https://www.wikidata.org/wiki/Q222903","display_name":"Multiplexing","level":2,"score":0.4444272518157959},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.4376087486743927},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.434885710477829},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.31527259945869446},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2980732023715973},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.1494598090648651},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/vtcspring.2016.7504144","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtcspring.2016.7504144","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 83rd Vehicular Technology Conference (VTC Spring)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W1548669759","https://openalex.org/W1985761548","https://openalex.org/W2055849441","https://openalex.org/W2128513990","https://openalex.org/W2133698785","https://openalex.org/W2137012645","https://openalex.org/W2137813581","https://openalex.org/W2146000945","https://openalex.org/W2168625863","https://openalex.org/W3106282754","https://openalex.org/W3149599232","https://openalex.org/W4285719527"],"related_works":["https://openalex.org/W2792339401","https://openalex.org/W2530747331","https://openalex.org/W2125564215","https://openalex.org/W3097525855","https://openalex.org/W1986382998","https://openalex.org/W2517776947","https://openalex.org/W2084482193","https://openalex.org/W2550283967","https://openalex.org/W2063393180","https://openalex.org/W2310122400"],"abstract_inverted_index":{"This":[0],"letter":[1],"studies":[2],"a":[3,39],"new":[4],"method":[5],"based":[6],"on":[7],"Bayesian":[8,66],"variational":[9,70],"inference":[10],"to":[11,57,75],"estimate":[12],"the":[13,27,49,54,60,65,77,84,88],"sparse":[14,28],"channel":[15,33,61],"parameters":[16,62],"in":[17,38,53],"large-scale":[18],"multiple-input-single-output":[19],"orthogonal":[20],"frequency":[21],"division":[22],"multiplexing":[23],"(MISO-OFDM)":[24],"systems.":[25],"Also,":[26],"common":[29],"support":[30],"of":[31,48],"different":[32],"impulse":[34],"responses,":[35],"which":[36],"results":[37,81],"block-":[40],"structured":[41],"model,":[42],"is":[43,51,73],"considered.":[44],"The":[45,79],"covariance":[46],"matrix":[47],"block":[50],"introduced":[52],"block-structured":[55],"model":[56],"effectively":[58],"recover":[59],"combining":[63],"with":[64],"hierarchical":[67],"structure.":[68],"Furthermore,":[69],"message-passing":[71],"(VMP)":[72],"applied":[74],"slove":[76],"problem.":[78],"simulation":[80],"show":[82],"that":[83],"proposed":[85],"algorithm":[86],"outperforms":[87],"traditional":[89],"ones.":[90]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}