{"id":"https://openalex.org/W2006032855","doi":"https://doi.org/10.1109/vtcfall.2013.6692345","title":"Partial Noise Value Aided Reduced K-Best Sphere Decoding","display_name":"Partial Noise Value Aided Reduced K-Best Sphere Decoding","publication_year":2013,"publication_date":"2013-09-01","ids":{"openalex":"https://openalex.org/W2006032855","doi":"https://doi.org/10.1109/vtcfall.2013.6692345","mag":"2006032855"},"language":"en","primary_location":{"id":"doi:10.1109/vtcfall.2013.6692345","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtcfall.2013.6692345","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE 78th Vehicular Technology Conference (VTC Fall)","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/A5100604344","display_name":"Xinyu Mao","orcid":"https://orcid.org/0000-0003-3077-1386"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xinyu Mao","raw_affiliation_strings":["School of Electrical and Computer Engineering, Peking University, Beijing, China","Sch. of Electr. & Comput. Eng., Peking Univ., Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Sch. of Electr. & Comput. Eng., Peking Univ., Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103008691","display_name":"Yuxin Cheng","orcid":"https://orcid.org/0000-0002-6494-0101"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuxin Cheng","raw_affiliation_strings":["School of Electrical and Computer Engineering, Peking University, Beijing, China","Sch. of Electr. & Comput. Eng., Peking Univ., Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Sch. of Electr. & Comput. Eng., Peking Univ., Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101824600","display_name":"Haige Xiang","orcid":"https://orcid.org/0000-0001-7620-5326"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haige Xiang","raw_affiliation_strings":["School of Electrical and Computer Engineering, Peking University, Beijing, China","Sch. of Electr. & Comput. Eng., Peking Univ., Beijing, China"],"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]},{"raw_affiliation_string":"Sch. of Electr. & Comput. Eng., Peking Univ., Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100604344"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.0777189,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10125","display_name":"Advanced Wireless Communication Techniques","score":1.0,"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/T10125","display_name":"Advanced Wireless Communication Techniques","score":1.0,"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/T11321","display_name":"Error Correcting Code Techniques","score":0.9994000196456909,"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/T10575","display_name":"Wireless Communication Networks Research","score":0.9987999796867371,"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/algorithm","display_name":"Algorithm","score":0.682483434677124},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.6328697800636292},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.5979002714157104},{"id":"https://openalex.org/keywords/mimo","display_name":"MIMO","score":0.5702385306358337},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5700543522834778},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.5439167022705078},{"id":"https://openalex.org/keywords/qam","display_name":"QAM","score":0.519719123840332},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49644213914871216},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.47450751066207886},{"id":"https://openalex.org/keywords/quadrature-amplitude-modulation","display_name":"Quadrature amplitude modulation","score":0.47205454111099243},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.46525436639785767},{"id":"https://openalex.org/keywords/transmission","display_name":"Transmission (telecommunications)","score":0.45176178216934204},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.43788617849349976},{"id":"https://openalex.org/keywords/bit-error-rate","display_name":"Bit error rate","score":0.4314999580383301},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4272667169570923},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.17467808723449707},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.17227652668952942},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.09247875213623047},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.0744519829750061}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.682483434677124},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.6328697800636292},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.5979002714157104},{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.5702385306358337},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5700543522834778},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.5439167022705078},{"id":"https://openalex.org/C59030546","wikidata":"https://www.wikidata.org/wiki/Q7265371","display_name":"QAM","level":5,"score":0.519719123840332},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49644213914871216},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.47450751066207886},{"id":"https://openalex.org/C32409245","wikidata":"https://www.wikidata.org/wiki/Q749753","display_name":"Quadrature amplitude modulation","level":4,"score":0.47205454111099243},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.46525436639785767},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.45176178216934204},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.43788617849349976},{"id":"https://openalex.org/C56296756","wikidata":"https://www.wikidata.org/wiki/Q840922","display_name":"Bit error rate","level":3,"score":0.4314999580383301},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4272667169570923},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.17467808723449707},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.17227652668952942},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.09247875213623047},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0744519829750061},{"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/vtcfall.2013.6692345","is_oa":false,"landing_page_url":"https://doi.org/10.1109/vtcfall.2013.6692345","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE 78th Vehicular Technology Conference (VTC Fall)","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":11,"referenced_works":["https://openalex.org/W2016896252","https://openalex.org/W2019524229","https://openalex.org/W2034675737","https://openalex.org/W2097736984","https://openalex.org/W2111626380","https://openalex.org/W2115084039","https://openalex.org/W2148978817","https://openalex.org/W2172028715","https://openalex.org/W2541204438","https://openalex.org/W2798333393","https://openalex.org/W3104795992"],"related_works":["https://openalex.org/W4390873927","https://openalex.org/W2159438609","https://openalex.org/W2900995485","https://openalex.org/W2147334234","https://openalex.org/W3196902411","https://openalex.org/W2139936226","https://openalex.org/W3026565890","https://openalex.org/W2064534496","https://openalex.org/W1970526599","https://openalex.org/W2161389097"],"abstract_inverted_index":{"This":[0],"article":[1],"focuses":[2],"on":[3],"reducing":[4],"the":[5,15,63,80,89,110,133,142,147,151,157,185,193],"complexity":[6,139,153,179,190],"of":[7,17,53,83,92,106,192],"K-best":[8],"sphere":[9],"decoding":[10],"(K-best":[11],"SD)":[12],"algorithm":[13,135,149,195],"for":[14,126],"detection":[16],"multiple-input":[18],"multiple-output":[19],"(MIMO)":[20],"systems.":[21],"One":[22],"common":[23],"reduction":[24,140,186],"method":[25],"is":[26,72,85,94,181],"that":[27,132],"one":[28,199],"or":[29,172],"more":[30,120],"selected":[31,200],"thresholds":[32],"are":[33,196],"set":[34],"to":[35,59,109,183],"cut":[36],"excess":[37],"nodes":[38],"with":[39],"partial":[40],"Euclidean":[41],"Distance":[42],"(PED)":[43],"larger":[44],"than":[45,198],"them.":[46],"For":[47],"a":[48,67,98,117],"long":[49],"time,":[50],"statistical":[51,81],"characteristic":[52,82],"noise":[54,65,84,93,103],"has":[55],"been":[56],"well":[57],"explored":[58],"generate":[60],"thresholds.":[61],"But":[62],"known":[64,90],"in":[66,113,166],"certain":[68],"specific":[69],"transmission":[70],"process":[71],"always":[73],"overlooked.":[74],"In":[75],"this":[76,127],"article,":[77],"not":[78],"only":[79],"calculated,":[86],"but":[87],"also":[88],"value":[91],"considered.":[95],"By":[96],"adding":[97],"parameter":[99],"determined":[100],"by":[101],"both":[102],"and":[104,119,188],"quality":[105],"service":[107],"(QoS)":[108],"smallest":[111],"PED":[112],"each":[114],"searching":[115],"layer,":[116],"tighter":[118],"suitable":[121],"threshold":[122],"can":[123],"be":[124],"calculated":[125],"layer.":[128],"Simulation":[129],"results":[130],"show":[131],"proposed":[134,148,182,194],"makes":[136],"an":[137],"efficient":[138],"while":[141,156],"performance":[143,162],"drops":[144,163],"little.":[145],"Specially,":[146],"reduces":[150],"computational":[152],"about":[154],"90\\%":[155],"bit":[158],"error":[159],"ratio":[160],"(BER)":[161],"around":[164],"10\\%":[165],"4-by-4":[167],"MIMO":[168],"systems":[169],"employing":[170],"16-QAM":[171],"64-QAM":[173],"modulation.":[174],"A":[175],"new":[176],"parameter,":[177],"half":[178,189],"point,":[180],"evaluate":[184],"effect,":[187],"points":[191],"better":[197],"original":[201],"algorithm.":[202]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}
