{"id":"https://openalex.org/W7204178626","doi":"https://doi.org/10.1109/isit62367.2026.11653983","title":"Quantized Sparse Regression Codes with Optimized OAMP Decoding","display_name":"Quantized Sparse Regression Codes with Optimized OAMP Decoding","publication_year":2026,"publication_date":"2026-06-01","ids":{"openalex":"https://openalex.org/W7204178626","doi":"https://doi.org/10.1109/isit62367.2026.11653983"},"language":"en","primary_location":{"id":"doi:10.1109/isit62367.2026.11653983","doi":"https://doi.org/10.1109/isit62367.2026.11653983","is_oa":true,"landing_page_url":"https://doi.org/10.1109/isit62367.2026.11653983","pdf_url":null,"source":{"id":"https://openalex.org/S4363604560","display_name":"IEEE International Symposium on Information Theory (ISIT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1109/isit62367.2026.11653983","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100585519","display_name":"Chengpin Luo","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I177738480","display_name":"Japan Advanced Institute of Science and Technology","ror":"https://ror.org/03frj4r98","country_code":"JP","type":"education","lineage":["https://openalex.org/I177738480"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Chengpin Luo","raw_affiliation_strings":["Japan Advanced Institute of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Japan Advanced Institute of Science and Technology","institution_ids":["https://openalex.org/I177738480"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004778561","display_name":"Brian M. Kurkoski","orcid":"https://orcid.org/0000-0003-4328-8684","observed_orcids":["https://orcid.org/0000-0003-4328-8684"]},"institutions":[{"id":"https://openalex.org/I177738480","display_name":"Japan Advanced Institute of Science and Technology","ror":"https://ror.org/03frj4r98","country_code":"JP","type":"education","lineage":["https://openalex.org/I177738480"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Brian M. Kurkoski","raw_affiliation_strings":["Japan Advanced Institute of Science and Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Japan Advanced Institute of Science and Technology","institution_ids":["https://openalex.org/I177738480"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5140742315","display_name":"Lei Liu","orcid":"https://orcid.org/0000-0002-0807-2135","observed_orcids":["https://orcid.org/0000-0002-0807-2135"]},"institutions":[{"id":"https://openalex.org/I76130692","display_name":"Zhejiang University","ror":"https://ror.org/00a2xv884","country_code":"CN","type":"education","lineage":["https://openalex.org/I76130692"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Liu","raw_affiliation_strings":["Zhejiang University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University","institution_ids":["https://openalex.org/I76130692"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.7914999723434448,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.7914999723434448,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11321","display_name":"Error Correcting Code Techniques","score":0.13009999692440033,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.009100000374019146,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/sparse-regression-codes","display_name":"sparse regression codes","score":0.9980000257492065},{"id":"https://openalex.org/keywords/clippers","display_name":"CLIPPERS","score":0.6740000247955322},{"id":"https://openalex.org/keywords/finite-length-performance","display_name":"finite-length performance","score":0.6940000057220459},{"id":"https://openalex.org/keywords/awgn-channel","display_name":"AWGN channel","score":0.7049999833106995},{"id":"https://openalex.org/keywords/hardware-implementation","display_name":"hardware implementation","score":0.4410000145435333}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5655999779701233},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5264999866485596},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.5054000020027161},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.36970001459121704},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3596000075340271},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.34040001034736633},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.3352999985218048},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.3248000144958496},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3237000107765198},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.32260000705718994},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.31769999861717224},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.30169999599456787},{"id":"https://openalex.org/C193969084","wikidata":"https://www.wikidata.org/wiki/Q7452500","display_name":"Sequential decoding","level":4,"score":0.2985000014305115},{"id":"https://openalex.org/C147764199","wikidata":"https://www.wikidata.org/wiki/Q6865248","display_name":"Minification","level":2,"score":0.2849000096321106},{"id":"https://openalex.org/C152877465","wikidata":"https://www.wikidata.org/wiki/Q208042","display_name":"Regression analysis","level":2,"score":0.28369998931884766},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.27250000834465027},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.26589998602867126},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.26339998841285706},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.25130000710487366},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2506999969482422}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit62367.2026.11653983","doi":"https://doi.org/10.1109/isit62367.2026.11653983","is_oa":true,"landing_page_url":"https://doi.org/10.1109/isit62367.2026.11653983","pdf_url":null,"source":{"id":"https://openalex.org/S4363604560","display_name":"IEEE International Symposium on Information Theory (ISIT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1109/isit62367.2026.11653983","doi":"https://doi.org/10.1109/isit62367.2026.11653983","is_oa":true,"landing_page_url":"https://doi.org/10.1109/isit62367.2026.11653983","pdf_url":null,"source":{"id":"https://openalex.org/S4363604560","display_name":"IEEE International Symposium on Information Theory (ISIT)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1837352444","https://openalex.org/W1909826856","https://openalex.org/W2039957496","https://openalex.org/W2082029531","https://openalex.org/W2088934832","https://openalex.org/W2092639489","https://openalex.org/W2129857026","https://openalex.org/W2150593711","https://openalex.org/W2166347904","https://openalex.org/W2610971674","https://openalex.org/W2747773209","https://openalex.org/W2759247683","https://openalex.org/W2944333051","https://openalex.org/W2945463326","https://openalex.org/W2963602028","https://openalex.org/W3008148299","https://openalex.org/W3097725224","https://openalex.org/W3169741318","https://openalex.org/W4248709896","https://openalex.org/W4285210099","https://openalex.org/W4289713206","https://openalex.org/W4396712613","https://openalex.org/W4402475369","https://openalex.org/W7126189054"],"related_works":["https://openalex.org/W7204212479","https://openalex.org/W2945531417","https://openalex.org/W2917706472","https://openalex.org/W2758729540","https://openalex.org/W2188006619","https://openalex.org/W2145002357","https://openalex.org/W7067129947","https://openalex.org/W2561045925","https://openalex.org/W2142244617","https://openalex.org/W2008919281"],"abstract_inverted_index":{"Sparse":[0],"regression":[1],"(SR)":[2],"codes":[3,16,74,76,87],"are":[4,81],"designed":[5],"to":[6,83],"enable":[7],"efficient":[8],"communication.":[9],"In":[10,49],"this":[11,50],"paper,":[12],"we":[13,21,52,93],"consider":[14],"SR":[15,24,73,86],"with":[17,33,77,105],"nonlinear":[18,23,55],"functions,":[19,60],"which":[20,61],"call":[22],"codes.":[25],"Previous":[26],"studies":[27],"have":[28],"shown":[29],"that":[30,70,95],"incorporating":[31],"clippers":[32,107],"appropriately":[34],"chosen":[35],"thresholds":[36],"can":[37,108],"significantly":[38],"improve":[39],"finite-length":[40],"performance":[41],"under":[42],"additive":[43],"white":[44],"Gaussian":[45],"noise":[46],"(AWGN)":[47],"channels.":[48],"work,":[51],"extend":[53],"the":[54,121,129],"framework":[56],"by":[57,111,127],"introducing":[58],"quantization":[59,116,123],"may":[62],"bring":[63],"benefits":[64],"for":[65],"hardware":[66],"implementation.":[67],"We":[68],"show":[69,94],"regularly":[71],"quantized":[72],"(SR":[75],"a":[78,96],"single":[79],"quantizer)":[80],"comparable":[82],"irregularly":[84],"clipped":[85],"at":[88],"code":[89],"rate":[90],"1.":[91],"Further,":[92],"gain":[97],"of":[98,120,133],"nearly":[99],"0.5":[100],"dB":[101],"over":[102],"irregular":[103,115,122],"clipping":[104],"4\u201310":[106],"be":[109],"achieved":[110],"employing":[112],"only":[113],"two":[114],"functions.":[117],"The":[118],"design":[119],"functions":[124],"is":[125],"obtained":[126],"optimizing":[128],"state":[130],"evolution":[131],"(SE)":[132],"an":[134],"orthogonal":[135],"approximate":[136],"message":[137],"passing":[138],"(OAMP)":[139],"decoder.":[140]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-08-26T00:00:00"}
