{"id":"https://openalex.org/W7214955660","doi":"https://doi.org/10.48550/arxiv.2609.36143","title":"Fundamental Limits of Dynamic Tracking and Communication: A Stationary Policy Formulation","display_name":"Fundamental Limits of Dynamic Tracking and Communication: A Stationary Policy Formulation","publication_year":2026,"publication_date":"2026-09-28","ids":{"openalex":"https://openalex.org/W7214955660","doi":"https://doi.org/10.48550/arxiv.2609.36143"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2609.36143","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.36143","pdf_url":"https://arxiv.org/pdf/2609.36143","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2609.36143","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108860206","display_name":"Mohammadreza Bakhshizadeh Mohajer","orcid":"https://orcid.org/0000-0002-8301-826X","observed_orcids":["https://orcid.org/0000-0002-8301-826X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mohajer, Mohammadreza Bakhshizadeh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054111453","display_name":"Luca Barletta","orcid":"https://orcid.org/0000-0003-4052-2092","observed_orcids":["https://orcid.org/0000-0003-4052-2092"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Barletta, Luca","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066257035","display_name":"Alex Dytso","orcid":"https://orcid.org/0000-0003-0625-5306","observed_orcids":["https://orcid.org/0000-0003-0625-5306"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dytso, Alex","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5153667681","display_name":"Giuseppe Caire","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Caire, Giuseppe","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"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/T10891","display_name":"Radar Systems and Signal Processing","score":0.7900000214576721,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10891","display_name":"Radar Systems and Signal Processing","score":0.7900000214576721,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.17299999296665192,"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"}},{"id":"https://openalex.org/T12879","display_name":"Distributed Sensor Networks and Detection Algorithms","score":0.005200000014156103,"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/integrated-sensing-and-communication","display_name":"integrated sensing and communication","score":0.9700000286102295},{"id":"https://openalex.org/keywords/dynamic-tracking","display_name":"dynamic tracking","score":0.5740000009536743},{"id":"https://openalex.org/keywords/rate-distortion-trade-off","display_name":"rate-distortion tradeoff","score":0.9049999713897705},{"id":"https://openalex.org/keywords/posterior-cramer-rao-bound","display_name":"posterior Cramer-Rao lower bound","score":0.9909999966621399},{"id":"https://openalex.org/keywords/covariance-control","display_name":"covariance control","score":0.6299999952316284},{"id":"https://openalex.org/keywords/outer-bound","display_name":"outer bound","score":0.6779999732971191},{"id":"https://openalex.org/keywords/extended-kalman-filter","display_name":"extended Kalman filter","score":0.8199999928474426},{"id":"https://openalex.org/keywords/multi-antenna-transmitter","display_name":"multi-antenna transmitter","score":0.5929999947547913}],"concepts":[{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.6481000185012817},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.6349999904632568},{"id":"https://openalex.org/C47446073","wikidata":"https://www.wikidata.org/wiki/Q5165890","display_name":"Control theory (sociology)","level":3,"score":0.555400013923645},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.5238999724388123},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.4593999981880188},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.4514999985694885},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.44760000705718994},{"id":"https://openalex.org/C181789720","wikidata":"https://www.wikidata.org/wiki/Q4812191","display_name":"Asymptotically optimal algorithm","level":2,"score":0.4323999881744385},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.4269999861717224},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4205999970436096},{"id":"https://openalex.org/C77553402","wikidata":"https://www.wikidata.org/wiki/Q13222579","display_name":"Upper and lower bounds","level":2,"score":0.41519999504089355},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.4009000062942505},{"id":"https://openalex.org/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.4000000059604645},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3531999886035919},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.34459999203681946},{"id":"https://openalex.org/C206833254","wikidata":"https://www.wikidata.org/wiki/Q5421817","display_name":"Extended Kalman filter","level":3,"score":0.3357999920845032},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.32330000400543213},{"id":"https://openalex.org/C47798520","wikidata":"https://www.wikidata.org/wiki/Q190157","display_name":"Transmitter","level":3,"score":0.30570000410079956},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.2766999900341034},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.26460000872612},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.26100000739097595},{"id":"https://openalex.org/C156778621","wikidata":"https://www.wikidata.org/wiki/Q1365748","display_name":"Spectrum (functional analysis)","level":2,"score":0.2581000030040741},{"id":"https://openalex.org/C183356978","wikidata":"https://www.wikidata.org/wiki/Q1779213","display_name":"Tracking error","level":3,"score":0.2563000023365021},{"id":"https://openalex.org/C137250428","wikidata":"https://www.wikidata.org/wiki/Q5178897","display_name":"Covariance function","level":3,"score":0.2513999938964844}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2609.36143","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.36143","pdf_url":"https://arxiv.org/pdf/2609.36143","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2609.36143","doi":"https://doi.org/10.48550/arxiv.2609.36143","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2609.36143","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2609.36143","doi":null,"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2609.36143","pdf_url":"https://arxiv.org/pdf/2609.36143","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"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":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7214955660.pdf","grobid_xml":"https://content.openalex.org/works/W7214955660.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4415313807","https://openalex.org/W4415367752","https://openalex.org/W4385819679","https://openalex.org/W4386057565","https://openalex.org/W2963417437","https://openalex.org/W4315605915","https://openalex.org/W7078792530","https://openalex.org/W67451300","https://openalex.org/W4221143525","https://openalex.org/W4401699133"],"abstract_inverted_index":{"We":[0,28,66,100,130],"study":[1],"a":[2,9,14,19,24,34,68,103,138,191],"dynamic":[3],"integrated":[4],"sensing-and-communication":[5],"problem":[6,85,124],"in":[7,62,126,146],"which":[8],"multi-antenna":[10],"transmitter":[11],"communicates":[12],"with":[13,161,190],"receiver":[15],"while":[16,172],"simultaneously":[17],"tracking":[18,60],"moving":[20],"target":[21,91],"governed":[22],"by":[23,54,72,143],"stable":[25],"Gauss--Markov":[26],"model.":[27],"formulate":[29],"the":[30,38,44,49,55,78,90,98,110,121,127,134,147,150,162,168,174],"sensing--communication":[31],"trade-off":[32],"as":[33],"rate--distortion":[35],"problem,":[36],"where":[37],"communication":[39,175],"rate":[40],"is":[41,52,86,93],"defined":[42],"through":[43,77],"Verd\u00fa--Han":[45],"information":[46,105],"spectrum":[47],"and":[48,64,107],"sensing":[50,151],"distortion":[51,76],"measured":[53],"long-run":[56],"minimum":[57],"mean":[58],"square":[59],"error":[61],"angle":[63],"distance.":[65],"construct":[67],"tractable":[69],"outer":[70,128,141,195],"region":[71],"lower":[73],"bounding":[74],"this":[75],"posterior":[79],"Cram\u00e9r--Rao":[80],"bound":[81,142],"(PCRB).":[82],"The":[83],"control":[84],"partially":[87],"observed":[88],"because":[89],"state":[92,106],"not":[94],"directly":[95],"available":[96],"to":[97],"transmitter.":[99],"therefore":[101],"introduce":[102],"belief-augmented":[104],"show,":[108],"under":[109,133],"stated":[111,135],"regularity":[112],"assumptions,":[113],"that":[114],"stationary":[115,164,169],"randomized":[116],"Markov":[117],"policies":[118],"suffice":[119],"for":[120,177],"covariance-based":[122],"scalarized":[123],"used":[125],"bound.":[129],"then":[131],"derive,":[132],"large-block":[136,148],"conditions,":[137],"Gaussian":[139,159,193],"covariance-control":[140,194],"showing":[144],"that,":[145],"regime,":[149],"belief":[152],"transition":[153],"becomes":[154],"asymptotically":[155,171],"covariance":[156,165],"sufficient;":[157],"consequently,":[158],"signaling":[160],"same":[163],"policy":[166],"preserves":[167],"PCRB":[170],"maximizing":[173],"reward":[176],"each":[178],"transmit":[179],"covariance.":[180],"Numerical":[181],"experiments":[182],"compare":[183],"an":[184],"extended":[185],"Kalman":[186],"filter-based":[187],"achievable":[188],"frontier":[189],"PCRB-based":[192],"frontier.":[196]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2026-10-01T00:00:00"}