{"id":"https://openalex.org/W4234721815","doi":"https://doi.org/10.1109/glocom.2014.7417209","title":"Novel Fast Iterative Decoding Threshold Estimation for Protograph-Based LDPC Convolutional Codes","display_name":"Novel Fast Iterative Decoding Threshold Estimation for Protograph-Based LDPC Convolutional Codes","publication_year":2014,"publication_date":"2014-12-01","ids":{"openalex":"https://openalex.org/W4234721815","doi":"https://doi.org/10.1109/glocom.2014.7417209"},"language":"en","primary_location":{"id":"doi:10.1109/glocom.2014.7417209","is_oa":false,"landing_page_url":"https://doi.org/10.1109/glocom.2014.7417209","pdf_url":null,"source":{"id":"https://openalex.org/S4363607712","display_name":"2015 IEEE Global Communications Conference (GLOBECOM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Global Communications Conference (GLOBECOM)","raw_type":"proceedings-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/A5003973886","display_name":"Tian Xia","orcid":"https://orcid.org/0009-0004-3376-9040"},"institutions":[{"id":"https://openalex.org/I121820613","display_name":"Louisiana State University","ror":"https://ror.org/05ect4e57","country_code":"US","type":"education","lineage":["https://openalex.org/I121820613"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tian Xia","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, Louisiana State University, Baton Rouge, LA, USA"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, Louisiana State University, Baton Rouge, LA, USA","institution_ids":["https://openalex.org/I121820613"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040614086","display_name":"Hsiao\u2010Chun Wu","orcid":"https://orcid.org/0000-0002-0178-1246"},"institutions":[{"id":"https://openalex.org/I121820613","display_name":"Louisiana State University","ror":"https://ror.org/05ect4e57","country_code":"US","type":"education","lineage":["https://openalex.org/I121820613"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hsiao-Chun Wu","raw_affiliation_strings":["School of Electrical Engineering and Computer Science, Louisiana State University, Baton Rouge, LA, USA"],"affiliations":[{"raw_affiliation_string":"School of Electrical Engineering and Computer Science, Louisiana State University, Baton Rouge, LA, USA","institution_ids":["https://openalex.org/I121820613"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100739582","display_name":"Hong Jiang","orcid":"https://orcid.org/0000-0003-2550-8401"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hong Jiang","raw_affiliation_strings":["Alcatel-Lucent Bell Labs, Murray Hill, NJ, USA"],"affiliations":[{"raw_affiliation_string":"Alcatel-Lucent Bell Labs, Murray Hill, NJ, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5003973886"],"corresponding_institution_ids":["https://openalex.org/I121820613"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.37604291,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"45","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11321","display_name":"Error Correcting Code Techniques","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11321","display_name":"Error Correcting Code Techniques","score":1.0,"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"}},{"id":"https://openalex.org/T10125","display_name":"Advanced Wireless Communication Techniques","score":0.9991000294685364,"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/T10796","display_name":"Cooperative Communication and Network Coding","score":0.9860000014305115,"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/low-density-parity-check-code","display_name":"Low-density parity-check code","score":0.7767572402954102},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.6698878407478333},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.6696007251739502},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.641044557094574},{"id":"https://openalex.org/keywords/additive-white-gaussian-noise","display_name":"Additive white Gaussian noise","score":0.5033723711967468},{"id":"https://openalex.org/keywords/convolutional-code","display_name":"Convolutional code","score":0.501448392868042},{"id":"https://openalex.org/keywords/upper-and-lower-bounds","display_name":"Upper and lower bounds","score":0.48624172806739807},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.4578174650669098},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2991991639137268},{"id":"https://openalex.org/keywords/white-noise","display_name":"White noise","score":0.21507462859153748},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.13669592142105103}],"concepts":[{"id":"https://openalex.org/C67692717","wikidata":"https://www.wikidata.org/wiki/Q187444","display_name":"Low-density parity-check code","level":3,"score":0.7767572402954102},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.6698878407478333},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6696007251739502},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.641044557094574},{"id":"https://openalex.org/C169334058","wikidata":"https://www.wikidata.org/wiki/Q353292","display_name":"Additive white Gaussian noise","level":3,"score":0.5033723711967468},{"id":"https://openalex.org/C157899210","wikidata":"https://www.wikidata.org/wiki/Q1395022","display_name":"Convolutional code","level":3,"score":0.501448392868042},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.48624172806739807},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.4578174650669098},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2991991639137268},{"id":"https://openalex.org/C112633086","wikidata":"https://www.wikidata.org/wiki/Q381287","display_name":"White noise","level":2,"score":0.21507462859153748},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.13669592142105103},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/glocom.2014.7417209","is_oa":false,"landing_page_url":"https://doi.org/10.1109/glocom.2014.7417209","pdf_url":null,"source":{"id":"https://openalex.org/S4363607712","display_name":"2015 IEEE Global Communications Conference (GLOBECOM)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Global Communications Conference (GLOBECOM)","raw_type":"proceedings-article"},{"id":"pmh:oai:repository.lsu.edu:eecs_pubs-3076","is_oa":false,"landing_page_url":"https://repository.lsu.edu/eecs_pubs/2074","pdf_url":null,"source":{"id":"https://openalex.org/S4210169993","display_name":"Civil War Book Review","issn_l":"1528-6592","issn":["1528-6592"],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310315936","host_organization_name":"Louisiana State University","host_organization_lineage":["https://openalex.org/P4310315936"],"host_organization_lineage_names":["Louisiana State University"],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Faculty Publications","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W91277888","https://openalex.org/W1536930200","https://openalex.org/W1972036717","https://openalex.org/W1988939003","https://openalex.org/W1991528082","https://openalex.org/W2017687288","https://openalex.org/W2085903266","https://openalex.org/W2101394529","https://openalex.org/W2118334163","https://openalex.org/W2123119950","https://openalex.org/W2160390925","https://openalex.org/W2169732368","https://openalex.org/W2172679141","https://openalex.org/W6603727012"],"related_works":["https://openalex.org/W2903058006","https://openalex.org/W4289655494","https://openalex.org/W1984351496","https://openalex.org/W2171154110","https://openalex.org/W2169741682","https://openalex.org/W2886957319","https://openalex.org/W2093568254","https://openalex.org/W4200289829","https://openalex.org/W2113434159","https://openalex.org/W2149798235"],"abstract_inverted_index":{"The":[0,159],"iterative":[1],"decoding":[2],"threshold":[3],"(IDT)":[4],"estimation":[5,42],"for":[6,52,141,174],"LDPC":[7],"convolutional":[8],"codes":[9],"(LDPC-CCs)":[10],"may":[11],"become":[12],"difficult":[13],"over":[14],"additive":[15],"white":[16],"Gaussian":[17],"noise":[18],"channels,":[19],"especially":[20],"when":[21],"the":[22,45,68,78,88,107,118,123,139,162,166,180],"termination":[23,148],"length":[24,149],"L":[25,150],"gets":[26],"very":[27],"large":[28,147],"or":[29,102],"even":[30],"approaches":[31],"infinity.":[32,158],"In":[33],"this":[34],"paper,":[35],"we":[36,60],"devise":[37],"a":[38,62,73,103],"novel":[39],"fast":[40],"IDT":[41,140],"scheme":[43],"using":[44,169],"protograph-based":[46,53],"extrinsic":[47],"information":[48,70],"transfer":[49],"(PEXIT)":[50],"analysis":[51],"LDPC-CCs.":[54],"Based":[55],"on":[56],"our":[57,170,183],"new":[58,172],"analysis,":[59],"propose":[61],"PEXIT-fast":[63],"algorithm":[64],"in":[65,96,177],"which":[66,151],"only":[67],"mutual":[69],"(MI)":[71],"of":[72,77,106,182],"posteriori":[74],"probability":[75],"(APP)":[76],"first":[79],"variable":[80],"node":[81],"will":[82],"be":[83,127,154,157],"monitored":[84],"to":[85,92,115,137,156],"determine":[86,138],"whether":[87],"current":[89],"E_b/N_0":[90],"(signal-energy-per-information-bit":[91],"noise-power-":[93],"spectral-density":[94],"ratio)":[95],"evaluation":[97],"is":[98,111],"an":[99,134,142,145],"upper":[100],"bound":[101,105],"lower":[104],"IDT.":[108],"Hence,":[109],"it":[110],"no":[112],"longer":[113],"necessary":[114],"get":[116],"through":[117],"whole":[119],"MI":[120],"evolution":[121],"and":[122,165],"computational":[124],"complexity":[125],"can":[126,152],"greatly":[128],"reduced":[129],"thereby.":[130],"We":[131],"also":[132,153],"design":[133],"efficient":[135],"approach":[136],"LDPC-CC":[143],"with":[144],"arbitrary":[146],"allowed":[155],"closeness":[160],"between":[161],"known":[163],"IDTs":[164,168],"estimated":[167],"proposed":[171],"method":[173],"several":[175],"LDPC-CCs":[176],"simulation":[178],"confirms":[179],"effectiveness":[181],"scheme.":[184]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
