{"id":"https://openalex.org/W7164826393","doi":"https://doi.org/10.1109/access.2026.3703759","title":"Transformer-Based Weighted Attention Coefficient Estimation for Augmented Envelope Memory Polynomial Predistortion","display_name":"Transformer-Based Weighted Attention Coefficient Estimation for Augmented Envelope Memory Polynomial Predistortion","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7164826393","doi":"https://doi.org/10.1109/access.2026.3703759"},"language":"en","primary_location":{"id":"doi:10.1109/access.2026.3703759","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3703759","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2026.3703759","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5041646643","display_name":"Mohammad Hossein Khazani","orcid":null},"institutions":[{"id":"https://openalex.org/I168635309","display_name":"University of Calgary","ror":"https://ror.org/03yjb2x39","country_code":"CA","type":"education","lineage":["https://openalex.org/I168635309"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Mohammad Hossein Khazani","raw_affiliation_strings":["Department of Electrical and Software Engineering, Schulich School of Engineering, iRadio Laboratory, University of Calgary, Calgary, AB, Canada"],"raw_orcid":"https://orcid.org/0009-0003-9944-7557","affiliations":[{"raw_affiliation_string":"Department of Electrical and Software Engineering, Schulich School of Engineering, iRadio Laboratory, University of Calgary, Calgary, AB, Canada","institution_ids":["https://openalex.org/I168635309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033466110","display_name":"Mohamed Helaoui","orcid":"https://orcid.org/0000-0002-1011-0348"},"institutions":[{"id":"https://openalex.org/I168635309","display_name":"University of Calgary","ror":"https://ror.org/03yjb2x39","country_code":"CA","type":"education","lineage":["https://openalex.org/I168635309"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Mohamed Helaoui","raw_affiliation_strings":["Department of Electrical and Software Engineering, Schulich School of Engineering, iRadio Laboratory, University of Calgary, Calgary, AB, Canada"],"raw_orcid":"https://orcid.org/0000-0002-1011-0348","affiliations":[{"raw_affiliation_string":"Department of Electrical and Software Engineering, Schulich School of Engineering, iRadio Laboratory, University of Calgary, Calgary, AB, Canada","institution_ids":["https://openalex.org/I168635309"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100766414","display_name":"Wenhua Chen","orcid":"https://orcid.org/0000-0002-9542-8709"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenhua Chen","raw_affiliation_strings":["Department of Electronic Engineering, Tsinghua University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-9542-8709","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086339362","display_name":"Fadhel M. Ghannouchi","orcid":"https://orcid.org/0000-0001-6788-1656"},"institutions":[{"id":"https://openalex.org/I168635309","display_name":"University of Calgary","ror":"https://ror.org/03yjb2x39","country_code":"CA","type":"education","lineage":["https://openalex.org/I168635309"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Fadhel M. Ghannouchi","raw_affiliation_strings":["Department of Electrical and Software Engineering, Schulich School of Engineering, iRadio Laboratory, University of Calgary, Calgary, AB, Canada"],"raw_orcid":"https://orcid.org/0000-0001-6788-1656","affiliations":[{"raw_affiliation_string":"Department of Electrical and Software Engineering, Schulich School of Engineering, iRadio Laboratory, University of Calgary, Calgary, AB, Canada","institution_ids":["https://openalex.org/I168635309"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.71409913,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"14","issue":null,"first_page":"91654","last_page":"91667"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.29600000381469727,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.29600000381469727,"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/T10323","display_name":"Analog and Mixed-Signal Circuit Design","score":0.12559999525547028,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T11248","display_name":"Advanced Power Amplifier Design","score":0.09359999746084213,"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/predistortion","display_name":"Predistortion","score":0.880299985408783},{"id":"https://openalex.org/keywords/polynomial","display_name":"Polynomial","score":0.570900022983551},{"id":"https://openalex.org/keywords/envelope","display_name":"Envelope (radar)","score":0.5049999952316284},{"id":"https://openalex.org/keywords/signal-processing","display_name":"Signal processing","score":0.3377000093460083},{"id":"https://openalex.org/keywords/control-theory","display_name":"Control theory (sociology)","score":0.31380000710487366},{"id":"https://openalex.org/keywords/scheme","display_name":"Scheme (mathematics)","score":0.2678000032901764}],"concepts":[{"id":"https://openalex.org/C2778587875","wikidata":"https://www.wikidata.org/wiki/Q7239686","display_name":"Predistortion","level":4,"score":0.880299985408783},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6746000051498413},{"id":"https://openalex.org/C90119067","wikidata":"https://www.wikidata.org/wiki/Q43260","display_name":"Polynomial","level":2,"score":0.570900022983551},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5601999759674072},{"id":"https://openalex.org/C65155139","wikidata":"https://www.wikidata.org/wiki/Q5380912","display_name":"Envelope (radar)","level":3,"score":0.5049999952316284},{"id":"https://openalex.org/C104267543","wikidata":"https://www.wikidata.org/wiki/Q208163","display_name":"Signal processing","level":3,"score":0.3377000093460083},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.31380000710487366},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28929999470710754},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.2815000116825104},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.28130000829696655},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2678000032901764},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.2624000012874603},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.2572999894618988},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.25220000743865967}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2026.3703759","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3703759","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:36efa800f4394f21ae56e92ecb8895bf","is_oa":false,"landing_page_url":"https://doaj.org/article/36efa800f4394f21ae56e92ecb8895bf","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 14, Pp 91654-91667 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2026.3703759","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2026.3703759","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7","score":0.45593175292015076}],"awards":[{"id":"https://openalex.org/G4742915892","display_name":null,"funder_award_id":"RT732800","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"}],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0,69],"paper":[1],"proposes":[2],"a":[3,66,92,98,145],"novel":[4],"behavioral":[5],"modeling":[6],"framework":[7],"applied":[8],"to":[9,40,54,112],"digital":[10],"predistortion":[11],"(DPD)":[12],"employing":[13],"Transformer":[14,45],"neural":[15,29],"networks":[16],"for":[17],"dynamic,":[18],"per-sample":[19],"coefficient":[20],"estimation":[21],"of":[22,76,84],"envelope":[23],"memory":[24,63],"polynomial":[25,58,78],"models.":[26],"Unlike":[27],"conventional":[28],"network":[30],"approaches":[31],"that":[32,105,142],"function":[33],"as":[34],"black-box":[35],"mappings":[36],"from":[37],"PA":[38,95],"output":[39],"clean":[41],"input,":[42],"the":[43,73,82,166],"proposed":[44],"Augmented":[46],"Envelope":[47],"Memory":[48,126],"Polynomial":[49],"(TAEMP)":[50],"leverages":[51],"multi-head":[52],"self-attention":[53],"determine":[55],"both":[56],"complex":[57],"coefficients":[59],"and":[60,133,153,170],"nonlinearity":[61],"order-specific":[62],"weights":[64],"on":[65,91],"sample-by-sample":[67],"basis.":[68],"physics-informed":[70],"approach":[71],"maintains":[72],"interpretable":[74],"structure":[75],"classical":[77],"models":[79],"while":[80],"enabling":[81],"tracking":[83],"time-varying":[85],"power":[86,156],"amplifier":[87],"dynamics.":[88],"Experimental":[89],"validation":[90],"GaN":[93],"Doherty":[94],"driven":[96],"by":[97],"60":[99],"MHz":[100],"5G":[101],"NR":[102],"signal":[103],"demonstrates":[104],"TAEMP":[106,143],"achieves":[107,144],"superior":[108],"spectral":[109,168],"performance":[110],"compared":[111],"five":[113],"baselines:":[114],"Deep":[115],"Neural":[116,120,130,136],"Network":[117,121,131,137],"(DNN),":[118],"Convolutional":[119],"(CNN),":[122],"Bidirectional":[123],"Long":[124],"Short-Term":[125],"(BiLSTM),":[127],"Block-Oriented":[128],"Time-Delay":[129,135],"(BOTDNN),":[132],"Phase-Normalized":[134],"(PNTDNN).":[138],"Hardware":[139],"measurements":[140],"confirm":[141],"normalized":[146],"mean":[147],"squared":[148],"error":[149],"(NMSE)":[150],"of\u221235.58":[151],"dB":[152],"adjacent":[154],"channel":[155],"ratio":[157],"(ACPR)":[158],"of\u221253.32/\u221253.36":[159],"dBc":[160],"with":[161],"1,683":[162],"learnable":[163],"parameters,":[164],"delivering":[165],"best":[167],"symmetry":[169],"compliance":[171],"among":[172],"all":[173],"evaluated":[174],"architectures":[175],"at":[176],"comparable":[177],"complexity.":[178]},"counts_by_year":[],"updated_date":"2026-06-24T06:17:17.354583","created_date":"2026-06-16T00:00:00"}