{"id":"https://openalex.org/W2795505757","doi":"https://doi.org/10.1109/iccchina.2017.8330421","title":"A linear predictive coding based compression algorithm for fronthaul link in C-RAN","display_name":"A linear predictive coding based compression algorithm for fronthaul link in C-RAN","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2795505757","doi":"https://doi.org/10.1109/iccchina.2017.8330421","mag":"2795505757"},"language":"en","primary_location":{"id":"doi:10.1109/iccchina.2017.8330421","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccchina.2017.8330421","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE/CIC International Conference on Communications in China (ICCC)","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/A5103071495","display_name":"Guangjin Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guangjin Chen","raw_affiliation_strings":["Key Laboratory of Universal Wireless Communications, Ministry of Education Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Universal Wireless Communications, Ministry of Education Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101151948","display_name":"Fangliao Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fangliao Yang","raw_affiliation_strings":["Key Laboratory of Universal Wireless Communications, Ministry of Education Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Universal Wireless Communications, Ministry of Education Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008455605","display_name":"Kai Niu","orcid":"https://orcid.org/0000-0002-8076-1867"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Niu","raw_affiliation_strings":["Key Laboratory of Universal Wireless Communications, Ministry of Education Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Universal Wireless Communications, Ministry of Education Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5048708984","display_name":"Chao Dong","orcid":"https://orcid.org/0000-0002-4922-7762"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Dong","raw_affiliation_strings":["Key Laboratory of Universal Wireless Communications, Ministry of Education Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Universal Wireless Communications, Ministry of Education Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103071495"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.43,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.67442932,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"18","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10148","display_name":"Advanced MIMO Systems Optimization","score":0.9995999932289124,"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":0.9995999932289124,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9980000257492065,"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/T10125","display_name":"Advanced Wireless Communication Techniques","score":0.996999979019165,"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/algorithm","display_name":"Algorithm","score":0.7193622589111328},{"id":"https://openalex.org/keywords/compression-ratio","display_name":"Compression ratio","score":0.5874081254005432},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5847640037536621},{"id":"https://openalex.org/keywords/code-excited-linear-prediction","display_name":"Code-excited linear prediction","score":0.5488831996917725},{"id":"https://openalex.org/keywords/telecommunications-link","display_name":"Telecommunications link","score":0.533607006072998},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.5161024928092957},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.5115707516670227},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.5018465518951416},{"id":"https://openalex.org/keywords/codebook","display_name":"Codebook","score":0.4503265619277954},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.4489825367927551},{"id":"https://openalex.org/keywords/coding-gain","display_name":"Coding gain","score":0.44107457995414734},{"id":"https://openalex.org/keywords/linear-predictive-coding","display_name":"Linear predictive coding","score":0.32675546407699585},{"id":"https://openalex.org/keywords/speech-coding","display_name":"Speech coding","score":0.24518510699272156},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.17022275924682617},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.12678682804107666},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08361935615539551}],"concepts":[{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.7193622589111328},{"id":"https://openalex.org/C25797200","wikidata":"https://www.wikidata.org/wiki/Q828137","display_name":"Compression ratio","level":3,"score":0.5874081254005432},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5847640037536621},{"id":"https://openalex.org/C105964291","wikidata":"https://www.wikidata.org/wiki/Q856184","display_name":"Code-excited linear prediction","level":4,"score":0.5488831996917725},{"id":"https://openalex.org/C138660444","wikidata":"https://www.wikidata.org/wiki/Q5607897","display_name":"Telecommunications link","level":2,"score":0.533607006072998},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.5161024928092957},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.5115707516670227},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.5018465518951416},{"id":"https://openalex.org/C127759330","wikidata":"https://www.wikidata.org/wiki/Q637416","display_name":"Codebook","level":2,"score":0.4503265619277954},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.4489825367927551},{"id":"https://openalex.org/C76862118","wikidata":"https://www.wikidata.org/wiki/Q1105671","display_name":"Coding gain","level":3,"score":0.44107457995414734},{"id":"https://openalex.org/C59883199","wikidata":"https://www.wikidata.org/wiki/Q1826438","display_name":"Linear predictive coding","level":3,"score":0.32675546407699585},{"id":"https://openalex.org/C13895895","wikidata":"https://www.wikidata.org/wiki/Q3270773","display_name":"Speech coding","level":2,"score":0.24518510699272156},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.17022275924682617},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.12678682804107666},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08361935615539551},{"id":"https://openalex.org/C171146098","wikidata":"https://www.wikidata.org/wiki/Q124192","display_name":"Automotive engineering","level":1,"score":0.0},{"id":"https://openalex.org/C511840579","wikidata":"https://www.wikidata.org/wiki/Q12757","display_name":"Internal combustion engine","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccchina.2017.8330421","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccchina.2017.8330421","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE/CIC International Conference on Communications in China (ICCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5600000023841858,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1990861143","https://openalex.org/W1998712632","https://openalex.org/W2001365282","https://openalex.org/W2068641562","https://openalex.org/W2099111195","https://openalex.org/W2136424765","https://openalex.org/W2210387432"],"related_works":["https://openalex.org/W2614570504","https://openalex.org/W4236018629","https://openalex.org/W2132539013","https://openalex.org/W3943236","https://openalex.org/W1499374905","https://openalex.org/W1593486778","https://openalex.org/W2173034275","https://openalex.org/W2105443669","https://openalex.org/W2014919663","https://openalex.org/W1586537451"],"abstract_inverted_index":{"This":[0],"paper":[1],"focuses":[2],"on":[3,85],"the":[4,48,55,59,62,72,86,90,102,110,179],"data":[5],"compression":[6,24,127,162,168],"for":[7,164,170],"fronthaul":[8],"link":[9],"in":[10,116],"cloud":[11],"radio":[12],"access":[13],"network":[14],"(C-RAN).":[15],"We":[16],"introduce":[17],"a":[18,65],"linear":[19,31,39,63],"predictive":[20],"coding":[21,78,81],"(LPC)":[22],"based":[23,84],"algorithm,":[25],"which":[26,172],"includes":[27],"three":[28],"main":[29],"modules,":[30],"predictor,":[32,64],"piecewise":[33,66,91],"quantizer":[34,67],"and":[35,107,112,166],"arithmetic":[36,80,105],"coding.":[37],"The":[38],"predictor":[40],"is":[41,68,82,98],"used":[42],"to":[43,54,70,100,139],"eliminate":[44],"redundancies":[45],"caused":[46],"by":[47],"correlations":[49],"of":[50,58,104],"LTE":[51],"signals.":[52],"According":[53],"distribution":[56],"characteristics":[57],"output":[60,87],"from":[61,89],"designed":[69],"decrease":[71],"quantization":[73],"noise.":[74],"To":[75],"get":[76],"extra":[77],"gain,":[79],"applied":[83],"codebook":[88],"quantizer.":[92],"Furthermore,":[93],"an":[94,148],"alphabet":[95],"reconstruction":[96],"scheme":[97,135],"proposed":[99],"reduce":[101],"complexity":[103],"encoding":[106],"decoding.":[108],"Omitting":[109],"up/down-sampling":[111],"low-pass":[113],"filtering":[114],"operation":[115],"traditional":[117,180],"schemes,":[118],"our":[119,134,157],"solution":[120],"has":[121,173],"simpler":[122],"structure,":[123],"but":[124],"demonstrates":[125],"better":[126],"performance":[128],"with":[129,178],"comparable":[130],"computational":[131],"complexity.":[132],"Remarkably,":[133],"presents":[136],"strong":[137],"flexibility":[138],"different":[140],"load":[141,145],"ratios.":[142],"Taking":[143],"40%":[144],"ratio":[146,163,169],"as":[147],"example,":[149],"within":[150],"2%":[151],"error":[152],"vector":[153],"magnitude":[154],"(EVM)":[155],"distortion,":[156],"algorithm":[158],"can":[159],"achieve":[160],"23%":[161],"uplink":[165],"17%":[167],"downlink,":[171],"nearly":[174],"15%":[175],"gain":[176],"compared":[177],"algorithm.":[181]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}