{"id":"https://openalex.org/W4393062696","doi":"https://doi.org/10.1109/gcwkshps58843.2023.10464444","title":"A Gradient Driven Graph Neural Network for Optimizing Precoding","display_name":"A Gradient Driven Graph Neural Network for Optimizing Precoding","publication_year":2023,"publication_date":"2023-12-04","ids":{"openalex":"https://openalex.org/W4393062696","doi":"https://doi.org/10.1109/gcwkshps58843.2023.10464444"},"language":"en","primary_location":{"id":"doi:10.1109/gcwkshps58843.2023.10464444","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/gcwkshps58843.2023.10464444","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Globecom Workshops (GC Wkshps)","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/A5100418969","display_name":"Zhang Li","orcid":"https://orcid.org/0000-0003-1989-6102"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Lin Zhang","raw_affiliation_strings":["School of Electronic and Information Engineering, Beihang University,Beijing,China,100191"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beihang University,Beijing,China,100191","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040178565","display_name":"Shengqian Han","orcid":"https://orcid.org/0000-0002-2085-3292"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengqian Han","raw_affiliation_strings":["School of Electronic and Information Engineering, Beihang University,Beijing,China,100191"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beihang University,Beijing,China,100191","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082950698","display_name":"Chenyang Yang","orcid":"https://orcid.org/0000-0003-0058-0765"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenyang Yang","raw_affiliation_strings":["School of Electronic and Information Engineering, Beihang University,Beijing,China,100191"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beihang University,Beijing,China,100191","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100421442","display_name":"Yang Li","orcid":"https://orcid.org/0000-0002-1751-1742"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Li","raw_affiliation_strings":["School of Electronic and Information Engineering, Beihang University,Beijing,China,100191"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, Beihang University,Beijing,China,100191","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100418969"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.3185,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.65504443,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"341","last_page":"346"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.7770000100135803,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10885","display_name":"Gene expression and cancer classification","score":0.7770000100135803,"subfield":{"id":"https://openalex.org/subfields/1312","display_name":"Molecular Biology"},"field":{"id":"https://openalex.org/fields/13","display_name":"Biochemistry, Genetics and Molecular Biology"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/precoding","display_name":"Precoding","score":0.6896147727966309},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6701172590255737},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.47658488154411316},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.47574612498283386},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3627150058746338},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.28012073040008545},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.2173670530319214},{"id":"https://openalex.org/keywords/mimo","display_name":"MIMO","score":0.15114030241966248}],"concepts":[{"id":"https://openalex.org/C160562895","wikidata":"https://www.wikidata.org/wiki/Q7239557","display_name":"Precoding","level":4,"score":0.6896147727966309},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6701172590255737},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.47658488154411316},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.47574612498283386},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3627150058746338},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.28012073040008545},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2173670530319214},{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.15114030241966248},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/gcwkshps58843.2023.10464444","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/gcwkshps58843.2023.10464444","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE Globecom Workshops (GC Wkshps)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1970830346","https://openalex.org/W2616867685","https://openalex.org/W2908498346","https://openalex.org/W2971598376","https://openalex.org/W2981598692","https://openalex.org/W3040589146","https://openalex.org/W3096252532","https://openalex.org/W3099684761","https://openalex.org/W3112170415","https://openalex.org/W3152787073","https://openalex.org/W3189854358","https://openalex.org/W3212630591","https://openalex.org/W4280508843","https://openalex.org/W4297733535","https://openalex.org/W4316661067","https://openalex.org/W4320029429","https://openalex.org/W4385801104"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W4281688526","https://openalex.org/W2152088989","https://openalex.org/W2756419127","https://openalex.org/W4366493479","https://openalex.org/W2401571617","https://openalex.org/W2905893439","https://openalex.org/W3135374966","https://openalex.org/W2953205382","https://openalex.org/W3154774209"],"abstract_inverted_index":{"Precoder":[0],"optimization":[1],"for":[2,99],"multi-user":[3],"multi-antenna":[4],"systems":[5],"with":[6,70],"the":[7,23,32,51,64,67,73,76,81,86,88,97,106,111,115],"objective":[8],"of":[9,25,58,60,66,80,126],"sum":[10,68],"rate":[11,69],"maximization":[12],"is":[13],"a":[14,45],"widely":[15],"recognized":[16],"challenging":[17],"problem.":[18],"Existing":[19],"work":[20],"has":[21],"demonstrated":[22],"effectiveness":[24],"graph":[26],"neural":[27],"networks":[28],"(GNNs)":[29],"in":[30,124],"learning":[31],"precoder,":[33,62],"and":[34,75,119,129],"various":[35],"GNNs":[36],"have":[37],"been":[38],"designed.":[39],"In":[40],"this":[41],"paper,":[42],"we":[43],"propose":[44],"gradient":[46,65],"driven":[47],"GNN":[48,90,108],"to":[49,72,95,114],"learn":[50,96],"precoding":[52,82],"policy.":[53,83],"It":[54],"incorporates":[55],"two":[56],"kinds":[57],"knowledge":[59],"optimizing":[61],"namely":[63],"respect":[71],"precoder":[74],"permutation":[77],"equivariant":[78],"property":[79],"By":[84],"leveraging":[85],"knowledge,":[87],"proposed":[89,107],"employs":[91],"an":[92],"attention":[93],"mechanism":[94],"weights":[98],"information":[100],"aggregation.":[101],"Simulation":[102],"results":[103],"show":[104],"that":[105],"can":[109],"achieve":[110],"performance":[112,123],"close":[113],"traditional":[116],"numerical":[117],"algorithm":[118],"exhibit":[120],"better":[121],"generalization":[122],"terms":[125],"both":[127],"users":[128],"antennas":[130],"than":[131],"baseline":[132],"GNNs.":[133]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-12-21T23:12:01.093139","created_date":"2025-10-10T00:00:00"}