{"id":"https://openalex.org/W7138236569","doi":"https://doi.org/10.48550/arxiv.2603.14325","title":"Fundamental Limits of CSI Compression in FDD Massive MIMO","display_name":"Fundamental Limits of CSI Compression in FDD Massive MIMO","publication_year":2026,"publication_date":"2026-03-15","ids":{"openalex":"https://openalex.org/W7138236569","doi":"https://doi.org/10.48550/arxiv.2603.14325"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.14325","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.14325","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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.14325","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5113145369","display_name":"Bumsu Park","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Park, Bumsu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129693337","display_name":"Youngmok Park","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Park, Youngmok","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125545373","display_name":"Chanho Park","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Park, Chanho","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129694075","display_name":"Namyoon Lee","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lee, Namyoon","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.8956000208854675,"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/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.8956000208854675,"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/T10125","display_name":"Advanced Wireless Communication Techniques","score":0.049800001084804535,"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.009100000374019146,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/channel-state-information","display_name":"Channel state information","score":0.6945000290870667},{"id":"https://openalex.org/keywords/lossless-compression","display_name":"Lossless compression","score":0.5461000204086304},{"id":"https://openalex.org/keywords/wideband","display_name":"Wideband","score":0.49889999628067017},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4794999957084656},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4528000056743622},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.4465000033378601},{"id":"https://openalex.org/keywords/mimo","display_name":"MIMO","score":0.43880000710487366},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.3930000066757202},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.3813000023365021}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6951000094413757},{"id":"https://openalex.org/C148063708","wikidata":"https://www.wikidata.org/wiki/Q5072511","display_name":"Channel state information","level":3,"score":0.6945000290870667},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.6603000164031982},{"id":"https://openalex.org/C81081738","wikidata":"https://www.wikidata.org/wiki/Q55542","display_name":"Lossless compression","level":3,"score":0.5461000204086304},{"id":"https://openalex.org/C2780202535","wikidata":"https://www.wikidata.org/wiki/Q4524457","display_name":"Wideband","level":2,"score":0.49889999628067017},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4794999957084656},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4528000056743622},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.4465000033378601},{"id":"https://openalex.org/C207987634","wikidata":"https://www.wikidata.org/wiki/Q176862","display_name":"MIMO","level":3,"score":0.43880000710487366},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.3930000066757202},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.3813000023365021},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.3684999942779541},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.3596000075340271},{"id":"https://openalex.org/C43126263","wikidata":"https://www.wikidata.org/wiki/Q128751","display_name":"Source code","level":2,"score":0.33899998664855957},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3327000141143799},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.3176000118255615},{"id":"https://openalex.org/C68649174","wikidata":"https://www.wikidata.org/wiki/Q1379116","display_name":"Base station","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.3009999990463257},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.2906999886035919},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.28619998693466187},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2806999981403351},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2791000008583069},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.27399998903274536},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2574999928474426}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.14325","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.14325","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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.14325","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.14325","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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Channel":[0],"state":[1,42,104],"information":[2],"(CSI)":[3],"feedback":[4,100],"in":[5],"frequency-division":[6],"duplex":[7],"(FDD)":[8],"massive":[9],"multiple-input":[10],"multiple-output":[11],"(MIMO)":[12],"systems":[13],"is":[14,196,206],"fundamentally":[15],"limited":[16],"by":[17,57,88,180,208],"the":[18,29,72,81,127,132,139,142,148,158,161,171,188,198,216,224],"high":[19],"dimensionality":[20],"of":[21,75,84,174],"wideband":[22,31],"channels.":[23],"In":[24],"this":[25,89,178],"paper,":[26],"we":[27,91],"model":[28,179,237],"stacked":[30],"CSI":[32,77,99,137,159,175,248],"vector":[33],"as":[34,120],"a":[35,39,52,58,97,121,152,209],"Gaussian-mixture":[36,93],"source":[37,154],"with":[38,64,106],"latent":[40],"geometry":[41,145],"that":[43,102,166,197,220,246],"represents":[44],"different":[45],"propagation":[46],"environments.":[47],"Each":[48],"component":[49],"corresponds":[50],"to":[51,165,228],"locally":[53],"stationary":[54],"regime":[55],"characterized":[56],"correlated":[59],"proper":[60],"complex":[61],"Gaussian":[62,85],"distribution":[63],"its":[65],"own":[66],"covariance":[67],"matrix.":[68],"This":[69],"representation":[70],"captures":[71],"multimodal":[73],"nature":[74],"practical":[76,98],"datasets":[78],"while":[79,233],"preserving":[80],"analytical":[82,182],"tractability":[83],"models.":[86],"Motivated":[87],"structure,":[90],"propose":[92],"transform":[94,163,230],"coding":[95,231],"(GMTC),":[96],"architecture":[101],"combines":[103],"inference":[105,241],"state-adaptive":[107,254],"TC.":[108],"The":[109],"mixture":[110,204],"parameters":[111],"are":[112],"learned":[113],"offline":[114],"from":[115],"channel":[116],"samples":[117],"and":[118,131,156,184,239],"stored":[119],"shared":[122],"statistical":[123],"dictionary":[124],"at":[125],"both":[126],"user":[128],"equipment":[129],"(UE)":[130],"base":[133],"station.":[134],"For":[135],"each":[136],"realization,":[138],"UE":[140],"identifies":[141],"most":[143],"likely":[144],"state,":[146],"encodes":[147],"corresponding":[149],"label":[150],"using":[151,160],"lossless":[153],"code,":[155],"compresses":[157],"Karhunen-Loeve":[162],"matched":[164],"state.":[167],"We":[168],"further":[169],"characterize":[170],"fundamental":[172],"limits":[173],"compression":[176,249],"under":[177],"deriving":[181],"converse":[183],"achievability":[185],"bounds":[186],"on":[187,215,258],"rate-distortion":[189],"(RD)":[190],"function.":[191],"A":[192],"key":[193],"structural":[194],"result":[195],"optimal":[199],"bit":[200],"allocation":[201],"across":[202],"all":[203],"components":[205],"governed":[207],"single":[210],"global":[211],"reverse-waterfilling":[212],"level.":[213],"Simulations":[214],"COST2100":[217],"dataset":[218],"show":[219],"GMTC":[221],"significantly":[222],"improves":[223],"RD":[225],"tradeoff":[226],"relative":[227],"neural":[229,260],"approaches":[232],"requiring":[234],"substantially":[235],"smaller":[236],"memory":[238],"lower":[240],"complexity.":[242],"These":[243],"results":[244],"indicate":[245],"near-optimal":[247],"can":[250],"be":[251],"achieved":[252],"through":[253],"TC":[255],"without":[256],"relying":[257],"large":[259],"encoders.":[261]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-18T00:00:00"}
