{"id":"https://openalex.org/W3111578708","doi":"https://doi.org/10.1109/icassp39728.2021.9415106","title":"Efficient Power Allocation Using Graph Neural Networks and Deep Algorithm Unfolding","display_name":"Efficient Power Allocation Using Graph Neural Networks and Deep Algorithm Unfolding","publication_year":2021,"publication_date":"2021-05-13","ids":{"openalex":"https://openalex.org/W3111578708","doi":"https://doi.org/10.1109/icassp39728.2021.9415106","mag":"3111578708"},"language":"en","primary_location":{"id":"doi:10.1109/icassp39728.2021.9415106","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9415106","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2012.02250","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059527667","display_name":"Arindam Chowdhury","orcid":"https://orcid.org/0000-0001-7298-1969"},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Arindam Chowdhury","raw_affiliation_strings":["Rice University,USA","Rice Univ (USA)"],"affiliations":[{"raw_affiliation_string":"Rice University,USA","institution_ids":["https://openalex.org/I74775410"]},{"raw_affiliation_string":"Rice Univ (USA)","institution_ids":["https://openalex.org/I74775410"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020627397","display_name":"Gunjan Verma","orcid":"https://orcid.org/0000-0001-6504-1960"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gunjan Verma","raw_affiliation_strings":["US Army&#x2019;s CCDC Army Research Laboratory,USA","[US Army\u2019s CCDC Army Research Laboratory, USA]"],"affiliations":[{"raw_affiliation_string":"US Army&#x2019;s CCDC Army Research Laboratory,USA","institution_ids":[]},{"raw_affiliation_string":"[US Army\u2019s CCDC Army Research Laboratory, USA]","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012972614","display_name":"Chirag Rao","orcid":"https://orcid.org/0000-0002-3786-6436"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chirag Rao","raw_affiliation_strings":["US Army&#x2019;s CCDC Army Research Laboratory,USA","[US Army\u2019s CCDC Army Research Laboratory, USA]"],"affiliations":[{"raw_affiliation_string":"US Army&#x2019;s CCDC Army Research Laboratory,USA","institution_ids":[]},{"raw_affiliation_string":"[US Army\u2019s CCDC Army Research Laboratory, USA]","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113663310","display_name":"Ananthram Swami","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ananthram Swami","raw_affiliation_strings":["US Army&#x2019;s CCDC Army Research Laboratory,USA","[US Army\u2019s CCDC Army Research Laboratory, USA]"],"affiliations":[{"raw_affiliation_string":"US Army&#x2019;s CCDC Army Research Laboratory,USA","institution_ids":[]},{"raw_affiliation_string":"[US Army\u2019s CCDC Army Research Laboratory, USA]","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012007074","display_name":"Santiago Segarra","orcid":"https://orcid.org/0000-0002-8408-9633"},"institutions":[{"id":"https://openalex.org/I74775410","display_name":"Rice University","ror":"https://ror.org/008zs3103","country_code":"US","type":"education","lineage":["https://openalex.org/I74775410"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Santiago Segarra","raw_affiliation_strings":["Rice University,USA","Rice Univ (USA)"],"affiliations":[{"raw_affiliation_string":"Rice University,USA","institution_ids":["https://openalex.org/I74775410"]},{"raw_affiliation_string":"Rice Univ (USA)","institution_ids":["https://openalex.org/I74775410"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5059527667"],"corresponding_institution_ids":["https://openalex.org/I74775410"],"apc_list":null,"apc_paid":null,"fwci":0.6371,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.69240925,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"4725","last_page":"4729"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10796","display_name":"Cooperative Communication and Network Coding","score":0.9993000030517578,"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/T10796","display_name":"Cooperative Communication and Network Coding","score":0.9993000030517578,"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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9987000226974487,"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/T11158","display_name":"Wireless Networks and Protocols","score":0.9965000152587891,"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/computer-science","display_name":"Computer science","score":0.6921652555465698},{"id":"https://openalex.org/keywords/parameterized-complexity","display_name":"Parameterized complexity","score":0.6329535245895386},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5966089963912964},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5735881328582764},{"id":"https://openalex.org/keywords/wireless-network","display_name":"Wireless network","score":0.5540435314178467},{"id":"https://openalex.org/keywords/wireless-ad-hoc-network","display_name":"Wireless ad hoc network","score":0.4810643196105957},{"id":"https://openalex.org/keywords/fading","display_name":"Fading","score":0.4555652141571045},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.43481117486953735},{"id":"https://openalex.org/keywords/gradient-descent","display_name":"Gradient descent","score":0.4286273717880249},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.42610305547714233},{"id":"https://openalex.org/keywords/wireless","display_name":"Wireless","score":0.4209745228290558},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3718182146549225},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.22910156846046448},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21731984615325928}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6921652555465698},{"id":"https://openalex.org/C165464430","wikidata":"https://www.wikidata.org/wiki/Q1570441","display_name":"Parameterized complexity","level":2,"score":0.6329535245895386},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5966089963912964},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5735881328582764},{"id":"https://openalex.org/C108037233","wikidata":"https://www.wikidata.org/wiki/Q11375","display_name":"Wireless network","level":3,"score":0.5540435314178467},{"id":"https://openalex.org/C94523657","wikidata":"https://www.wikidata.org/wiki/Q4085781","display_name":"Wireless ad hoc network","level":3,"score":0.4810643196105957},{"id":"https://openalex.org/C81978471","wikidata":"https://www.wikidata.org/wiki/Q1196572","display_name":"Fading","level":3,"score":0.4555652141571045},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.43481117486953735},{"id":"https://openalex.org/C153258448","wikidata":"https://www.wikidata.org/wiki/Q1199743","display_name":"Gradient descent","level":3,"score":0.4286273717880249},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.42610305547714233},{"id":"https://openalex.org/C555944384","wikidata":"https://www.wikidata.org/wiki/Q249","display_name":"Wireless","level":2,"score":0.4209745228290558},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3718182146549225},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.22910156846046448},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21731984615325928},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"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/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1109/icassp39728.2021.9415106","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp39728.2021.9415106","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2012.02250","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2012.02250","pdf_url":"https://arxiv.org/pdf/2012.02250","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:3111578708","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2012.02250","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2012.02250","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2012.02250","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"},{"id":"doi:10.17023/g7gv-t367","is_oa":true,"landing_page_url":"https://doi.org/10.17023/g7gv-t367","pdf_url":null,"source":{"id":"https://openalex.org/S7407051697","display_name":"IEEE RESOURCE CENTERS","issn_l":null,"issn":[],"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":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2012.02250","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2012.02250","pdf_url":"https://arxiv.org/pdf/2012.02250","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3111578708.pdf","grobid_xml":"https://content.openalex.org/works/W3111578708.grobid-xml"},"referenced_works_count":39,"referenced_works":["https://openalex.org/W1564814491","https://openalex.org/W1662382123","https://openalex.org/W1970830346","https://openalex.org/W1995875735","https://openalex.org/W2005972443","https://openalex.org/W2100755644","https://openalex.org/W2111848267","https://openalex.org/W2118103795","https://openalex.org/W2144000019","https://openalex.org/W2616867685","https://openalex.org/W2797462110","https://openalex.org/W2798598284","https://openalex.org/W2883094398","https://openalex.org/W2886374543","https://openalex.org/W2892685897","https://openalex.org/W2943079819","https://openalex.org/W2945634986","https://openalex.org/W2963102871","https://openalex.org/W2963358464","https://openalex.org/W2964015378","https://openalex.org/W2964321699","https://openalex.org/W2971598376","https://openalex.org/W2984005789","https://openalex.org/W2995038946","https://openalex.org/W3006475512","https://openalex.org/W3011730771","https://openalex.org/W3012413020","https://openalex.org/W3012969853","https://openalex.org/W3045955967","https://openalex.org/W3088683473","https://openalex.org/W3108591189","https://openalex.org/W6637178625","https://openalex.org/W6677645113","https://openalex.org/W6720006811","https://openalex.org/W6726873649","https://openalex.org/W6746015598","https://openalex.org/W6769829701","https://openalex.org/W6771584377","https://openalex.org/W6783148041"],"related_works":["https://openalex.org/W3161818956","https://openalex.org/W3152787073","https://openalex.org/W3035670845","https://openalex.org/W2616867685","https://openalex.org/W3176877194","https://openalex.org/W3157343176","https://openalex.org/W2997137281","https://openalex.org/W2972816997","https://openalex.org/W2996854310","https://openalex.org/W2003309237","https://openalex.org/W2532583274","https://openalex.org/W1602070771","https://openalex.org/W1510033250","https://openalex.org/W3007940425","https://openalex.org/W2090251470","https://openalex.org/W1569642472","https://openalex.org/W3200145345","https://openalex.org/W2169705015","https://openalex.org/W1991707765","https://openalex.org/W2914172564"],"abstract_inverted_index":{"We":[0],"study":[1],"the":[2,27,31,60,67,72,89,106,118],"problem":[3],"of":[4,30,88,101,125],"optimal":[5],"power":[6,90],"allocation":[7,91],"in":[8,71],"a":[9,21,80],"single-hop":[10],"ad":[11],"hoc":[12],"wireless":[13,73,123],"network.":[14,74],"In":[15],"solving":[16],"this":[17],"problem,":[18],"we":[19,41],"propose":[20],"hybrid":[22],"neural":[23,56],"architecture":[24],"inspired":[25],"by":[26,66],"algorithmic":[28],"unfolding":[29],"iterative":[32],"weighted":[33],"minimum":[34],"mean":[35],"squared":[36],"error":[37],"(WMMSE)":[38],"method,":[39],"that":[40,100],"denote":[42],"as":[43],"unfolded":[44],"WMMSE":[45,102],"(UWMMSE).":[46],"The":[47],"learnable":[48],"weights":[49],"within":[50],"UWMMSE":[51,95],"are":[52,64,77],"parameterized":[53],"using":[54],"graph":[55],"networks":[57,124],"(GNNs),":[58],"where":[59],"time-varying":[61],"underlying":[62],"graphs":[63],"given":[65],"fading":[68],"interference":[69],"coefficients":[70],"These":[75],"GNNs":[76],"trained":[78],"through":[79,113],"gradient":[81],"descent":[82],"approach":[83],"based":[84],"on":[85],"multiple":[86],"instances":[87],"problem.":[92],"Once":[93],"trained,":[94],"achieves":[96],"performance":[97],"comparable":[98],"to":[99,122],"while":[103],"significantly":[104],"reducing":[105],"computational":[107],"complexity.":[108],"This":[109],"phenomenon":[110],"is":[111],"illustrated":[112],"numerical":[114],"experiments":[115],"along":[116],"with":[117],"robustness":[119],"and":[120,128],"generalization":[121],"different":[126],"densities":[127],"sizes.":[129]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
