{"id":"https://openalex.org/W3190138134","doi":"https://doi.org/10.1109/icc42927.2021.9500996","title":"Deep Joint Source Channel Coding for Wireless Image Transmission with OFDM","display_name":"Deep Joint Source Channel Coding for Wireless Image Transmission with OFDM","publication_year":2021,"publication_date":"2021-06-01","ids":{"openalex":"https://openalex.org/W3190138134","doi":"https://doi.org/10.1109/icc42927.2021.9500996","mag":"3190138134"},"language":"en","primary_location":{"id":"doi:10.1109/icc42927.2021.9500996","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc42927.2021.9500996","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2021 - IEEE International Conference on Communications","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060010918","display_name":"Mingyu Yang","orcid":"https://orcid.org/0000-0003-1301-6493"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mingyu Yang","raw_affiliation_strings":["University of Michigan, Ann Arbor, USA"],"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076857062","display_name":"Chenghong Bian","orcid":"https://orcid.org/0000-0002-0534-7076"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Chenghong Bian","raw_affiliation_strings":["University of Michigan, Ann Arbor, USA"],"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014196508","display_name":"Hun-Seok Kim","orcid":"https://orcid.org/0000-0002-6658-5502"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hun-Seok Kim","raw_affiliation_strings":["University of Michigan, Ann Arbor, USA"],"affiliations":[{"raw_affiliation_string":"University of Michigan, Ann Arbor, USA","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5060010918"],"corresponding_institution_ids":["https://openalex.org/I27837315"],"apc_list":null,"apc_paid":null,"fwci":8.4485,"has_fulltext":false,"cited_by_count":91,"citation_normalized_percentile":{"value":0.98057179,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":100},"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/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T12131","display_name":"Wireless Signal Modulation Classification","score":0.9997000098228455,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9965999722480774,"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"}},{"id":"https://openalex.org/T10860","display_name":"Speech and Audio Processing","score":0.9965000152587891,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7820945978164673},{"id":"https://openalex.org/keywords/orthogonal-frequency-division-multiplexing","display_name":"Orthogonal frequency-division multiplexing","score":0.7537956237792969},{"id":"https://openalex.org/keywords/baseband","display_name":"Baseband","score":0.6419222950935364},{"id":"https://openalex.org/keywords/fading","display_name":"Fading","score":0.5443896055221558},{"id":"https://openalex.org/keywords/multipath-propagation","display_name":"Multipath propagation","score":0.5189125537872314},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.42423075437545776},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.3972495198249817},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.34064948558807373},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.33982592821121216},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3265635371208191},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.18796631693840027},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09246432781219482},{"id":"https://openalex.org/keywords/bandwidth","display_name":"Bandwidth (computing)","score":0.0791301429271698}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7820945978164673},{"id":"https://openalex.org/C40409654","wikidata":"https://www.wikidata.org/wiki/Q375889","display_name":"Orthogonal frequency-division multiplexing","level":3,"score":0.7537956237792969},{"id":"https://openalex.org/C65165936","wikidata":"https://www.wikidata.org/wiki/Q575784","display_name":"Baseband","level":3,"score":0.6419222950935364},{"id":"https://openalex.org/C81978471","wikidata":"https://www.wikidata.org/wiki/Q1196572","display_name":"Fading","level":3,"score":0.5443896055221558},{"id":"https://openalex.org/C161218011","wikidata":"https://www.wikidata.org/wiki/Q11827794","display_name":"Multipath propagation","level":3,"score":0.5189125537872314},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.42423075437545776},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.3972495198249817},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.34064948558807373},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.33982592821121216},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3265635371208191},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.18796631693840027},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09246432781219482},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0791301429271698}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc42927.2021.9500996","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc42927.2021.9500996","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2021 - IEEE International Conference on Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1995875735","https://openalex.org/W2098717665","https://openalex.org/W2106550864","https://openalex.org/W2152744465","https://openalex.org/W2154181206","https://openalex.org/W2157331557","https://openalex.org/W2163605009","https://openalex.org/W2734408173","https://openalex.org/W2779699222","https://openalex.org/W2808769300","https://openalex.org/W2886374543","https://openalex.org/W2897042325","https://openalex.org/W2936697624","https://openalex.org/W2946889564","https://openalex.org/W2951542323","https://openalex.org/W2963073614","https://openalex.org/W2963174256","https://openalex.org/W2963403868","https://openalex.org/W2963889719","https://openalex.org/W2964121960","https://openalex.org/W2964198392","https://openalex.org/W2971153810","https://openalex.org/W2976657312","https://openalex.org/W2998038461","https://openalex.org/W3014802836","https://openalex.org/W3016715915","https://openalex.org/W4385245566","https://openalex.org/W6637373629","https://openalex.org/W6684191040","https://openalex.org/W6729966448","https://openalex.org/W6739901393","https://openalex.org/W6761632846"],"related_works":["https://openalex.org/W2376969857","https://openalex.org/W207732638","https://openalex.org/W2801592279","https://openalex.org/W4252788403","https://openalex.org/W2171869298","https://openalex.org/W1497654841","https://openalex.org/W2034040913","https://openalex.org/W2257001073","https://openalex.org/W2587688171","https://openalex.org/W1992602584"],"abstract_inverted_index":{"We":[0],"present":[1],"a":[2],"deep":[3],"learning":[4,55,118],"based":[5],"joint":[6],"source":[7,38,62,140],"channel":[8,64,94,142,167],"coding":[9,65,143],"(JSCC)":[10],"scheme":[11],"for":[12,44,60,165],"wireless":[13],"image":[14],"transmission":[15],"over":[16],"multipath":[17,74,93],"fading":[18,75],"channels":[19],"with":[20,73,86,149],"non-linear":[21,160],"signal":[22,98,161],"clipping.":[23],"The":[24,51,77],"proposed":[25,52],"encoder":[26],"and":[27,34,63,96,141,147],"decoder":[28],"use":[29],"convolutional":[30],"neural":[31],"networks":[32],"(CNN)":[33],"directly":[35],"map":[36],"the":[37,58,92,116,122,173,178],"images":[39],"to":[40,71,126,156],"complex-valued":[41],"baseband":[42,112],"samples":[43],"orthogonal":[45],"frequency":[46],"division":[47],"multiplexing":[48],"(OFDM)":[49],"transmission.":[50],"model-driven":[53],"machine":[54,117],"approach":[56],"eliminates":[57],"need":[59],"separate":[61,139],"while":[66],"integrating":[67],"an":[68,127],"OFDM":[69,97,111,164],"datapath":[70],"cope":[72],"channels.":[76],"end-to-end":[78],"JSCC":[79],"communication":[80],"system":[81],"combines":[82],"trainable":[83],"CNN":[84],"layers":[85,90],"non-trainable":[87],"but":[88,138],"differentiable":[89],"representing":[91],"model":[95,174],"processing":[99,113],"blocks.":[100],"Our":[101,130],"results":[102],"show":[103],"that":[104,135,169],"injecting":[105],"domain":[106],"expert":[107],"knowledge":[108],"by":[109],"incorporating":[110],"blocks":[114],"into":[115],"framework":[119],"significantly":[120],"enhances":[121],"overall":[123],"performance":[124],"compared":[125],"unstructured":[128],"CNN.":[129],"method":[131,153],"outperforms":[132],"conventional":[133],"schemes":[134],"employ":[136],"state-of-the-art":[137],"such":[144],"as":[145],"BPG":[146],"LDPC":[148],"OFDM.":[150],"Moreover,":[151],"our":[152],"is":[154],"shown":[155],"be":[157],"robust":[158],"against":[159],"clipping":[162],"in":[163],"various":[166],"conditions":[168],"do":[170],"not":[171],"match":[172],"parameter":[175],"used":[176],"during":[177],"training.":[179]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":27},{"year":2024,"cited_by_count":24},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":17},{"year":2021,"cited_by_count":3}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}
