{"id":"https://openalex.org/W4206138254","doi":"https://doi.org/10.1109/ic-nidc54101.2021.9660432","title":"Data-Driven Receiver for OTFS System with Deep Learning","display_name":"Data-Driven Receiver for OTFS System with Deep Learning","publication_year":2021,"publication_date":"2021-11-17","ids":{"openalex":"https://openalex.org/W4206138254","doi":"https://doi.org/10.1109/ic-nidc54101.2021.9660432"},"language":"en","primary_location":{"id":"doi:10.1109/ic-nidc54101.2021.9660432","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ic-nidc54101.2021.9660432","pdf_url":null,"source":{"id":"https://openalex.org/S4363608589","display_name":"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","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":"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","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/A5100624318","display_name":"Qingyu Li","orcid":"https://orcid.org/0000-0003-4638-4401"},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qingyu Li","raw_affiliation_strings":["BISTU,School of Information Communication Engineering,Beijing,China,100192"],"affiliations":[{"raw_affiliation_string":"BISTU,School of Information Communication Engineering,Beijing,China,100192","institution_ids":["https://openalex.org/I78675632"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5014382593","display_name":"Yi Gong","orcid":"https://orcid.org/0000-0002-6291-8429"},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Gong","raw_affiliation_strings":["BISTU,School of Information Communication Engineering,Beijing,China,100192"],"affiliations":[{"raw_affiliation_string":"BISTU,School of Information Communication Engineering,Beijing,China,100192","institution_ids":["https://openalex.org/I78675632"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059015552","display_name":"Fanke Meng","orcid":"https://orcid.org/0009-0002-0385-6800"},"institutions":[{"id":"https://openalex.org/I4210153211","display_name":"Hoopes Vision","ror":"https://ror.org/05ws0rr53","country_code":"US","type":"facility","lineage":["https://openalex.org/I4210153211"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Fanke Meng","raw_affiliation_strings":["Beijing Hoopox Information and Technology Co., Ltd"],"affiliations":[{"raw_affiliation_string":"Beijing Hoopox Information and Technology Co., Ltd","institution_ids":["https://openalex.org/I4210153211"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5050256911","display_name":"Zhan Xu","orcid":"https://orcid.org/0000-0001-5301-9600"},"institutions":[{"id":"https://openalex.org/I78675632","display_name":"Beijing Information Science & Technology University","ror":"https://ror.org/04xnqep60","country_code":"CN","type":"education","lineage":["https://openalex.org/I78675632"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhan Xu","raw_affiliation_strings":["BISTU,School of Information Communication Engineering,Beijing,China,100192"],"affiliations":[{"raw_affiliation_string":"BISTU,School of Information Communication Engineering,Beijing,China,100192","institution_ids":["https://openalex.org/I78675632"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100624318"],"corresponding_institution_ids":["https://openalex.org/I78675632"],"apc_list":null,"apc_paid":null,"fwci":4.3274,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.96538321,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"172","last_page":"176"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11873","display_name":"PAPR reduction in OFDM","score":0.9998999834060669,"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/T11873","display_name":"PAPR reduction in OFDM","score":0.9998999834060669,"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/T10205","display_name":"Advanced Fiber Optic Sensors","score":0.9850000143051147,"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/T10232","display_name":"Optical Network Technologies","score":0.9847000241279602,"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/robustness","display_name":"Robustness (evolution)","score":0.7623815536499023},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6730590462684631},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5369884967803955},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5235944986343384},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.48919036984443665},{"id":"https://openalex.org/keywords/data-driven","display_name":"Data-driven","score":0.4762268662452698},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.4674212634563446},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4494372308254242},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3791186213493347},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.34262436628341675},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.20379558205604553},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11744660139083862},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.11584961414337158}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7623815536499023},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6730590462684631},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5369884967803955},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5235944986343384},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.48919036984443665},{"id":"https://openalex.org/C2780440489","wikidata":"https://www.wikidata.org/wiki/Q5227278","display_name":"Data-driven","level":2,"score":0.4762268662452698},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.4674212634563446},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4494372308254242},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3791186213493347},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.34262436628341675},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.20379558205604553},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11744660139083862},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.11584961414337158},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ic-nidc54101.2021.9660432","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ic-nidc54101.2021.9660432","pdf_url":null,"source":{"id":"https://openalex.org/S4363608589","display_name":"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","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":"2021 7th IEEE International Conference on Network Intelligence and Digital Content (IC-NIDC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G5087533434","display_name":null,"funder_award_id":"2121YJPY224","funder_id":"https://openalex.org/F4320326666","funder_display_name":"Beijing Information Science and Technology University"}],"funders":[{"id":"https://openalex.org/F4320326666","display_name":"Beijing Information Science and Technology University","ror":"https://ror.org/04xnqep60"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2612254130","https://openalex.org/W2888002205","https://openalex.org/W2938563145","https://openalex.org/W2962951066","https://openalex.org/W2963190722","https://openalex.org/W2963817362","https://openalex.org/W3009071884","https://openalex.org/W3020081544","https://openalex.org/W3082571270","https://openalex.org/W3088034552","https://openalex.org/W3128040705","https://openalex.org/W3128173373","https://openalex.org/W3172410657","https://openalex.org/W3179436782"],"related_works":["https://openalex.org/W3162204513","https://openalex.org/W2371138613","https://openalex.org/W2048963458","https://openalex.org/W43109613","https://openalex.org/W2359952343","https://openalex.org/W2239445980","https://openalex.org/W2080152487","https://openalex.org/W3083152911","https://openalex.org/W3022347918","https://openalex.org/W3201343217"],"abstract_inverted_index":{"Recently":[0],"researches":[1],"about":[2],"receiver":[3,17,42,55,107,123],"structures":[4],"for":[5,56,96,127],"orthogonal":[6],"time-frequency":[7],"space":[8],"(OTFS)":[9],"have":[10],"been":[11],"received":[12],"widespread":[13],"attention.":[14],"Previous":[15],"OTFS":[16,41,57,128],"algorithms":[18],"are":[19,100],"based":[20,124],"on":[21,125],"model-driven,":[22],"which":[23,76,99],"would":[24],"lead":[25],"to":[26,61],"complex":[27],"structures.":[28],"Motivated":[29],"by":[30],"recent":[31],"advances":[32],"in":[33,80,103],"data-driven":[34,40,54,122],"receivers,":[35],"this":[36,67],"paper":[37],"proposes":[38],"a":[39,44,110],"with":[43],"deep":[45,73],"neural":[46],"network":[47],"(DNN).":[48],"We":[49],"demonstrate":[50],"that":[51,119],"the":[52,70,85,104,120],"proposed":[53,86,121],"can":[58,88,129],"be":[59],"generalized":[60],"different":[62],"high":[63],"mobility":[64],"scenarios.":[65],"Specifically,":[66],"scheme":[68],"combines":[69],"power":[71],"of":[72,106,113],"learning":[74],"(DL),":[75],"is":[77],"widely":[78],"used":[79],"various":[81],"fields.":[82],"With":[83],"DL,":[84],"algorithm":[87],"achieve":[89,130],"excellent":[90],"robustness":[91],"and":[92],"strong":[93],"generalization":[94],"ability":[95],"channel":[97],"parameters,":[98],"ubiquitous":[101],"challenges":[102],"design":[105],"algorithms.":[108],"Through":[109],"good":[111],"deal":[112],"numerical":[114],"experiments,":[115],"simulation":[116],"results":[117],"show":[118],"DNN":[126],"superior":[131],"performance":[132],"than":[133],"comparison":[134],"methods.":[135]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":3}],"updated_date":"2026-02-25T08:12:03.925757","created_date":"2025-10-10T00:00:00"}