{"id":"https://openalex.org/W3160268064","doi":"https://doi.org/10.1109/wcncw49093.2021.9420004","title":"A Reinforcement Learning Based Decoding Method of Short Polar Codes","display_name":"A Reinforcement Learning Based Decoding Method of Short Polar Codes","publication_year":2021,"publication_date":"2021-03-29","ids":{"openalex":"https://openalex.org/W3160268064","doi":"https://doi.org/10.1109/wcncw49093.2021.9420004","mag":"3160268064"},"language":"en","primary_location":{"id":"doi:10.1109/wcncw49093.2021.9420004","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcncw49093.2021.9420004","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Wireless Communications and Networking Conference Workshops (WCNCW)","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/A5079099587","display_name":"Jian Gao","orcid":"https://orcid.org/0000-0001-5113-1551"},"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":"Jian Gao","raw_affiliation_strings":["Key Laboratory of Universal Wireless Communication, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Universal Wireless Communication, 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/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 Communication, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Universal Wireless Communication, 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":2,"corresponding_author_ids":["https://openalex.org/A5079099587"],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":0.4584,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.64146817,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"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/T11321","display_name":"Error Correcting Code Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11321","display_name":"Error Correcting Code Techniques","score":0.9998999834060669,"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/T11269","display_name":"Algorithms and Data Compression","score":0.9926999807357788,"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/T10125","display_name":"Advanced Wireless Communication Techniques","score":0.9861999750137329,"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/reinforcement-learning","display_name":"Reinforcement learning","score":0.8678920865058899},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.8673495650291443},{"id":"https://openalex.org/keywords/markov-decision-process","display_name":"Markov decision process","score":0.7708566784858704},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7298948168754578},{"id":"https://openalex.org/keywords/sequential-decoding","display_name":"Sequential decoding","score":0.7138395309448242},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.5486149191856384},{"id":"https://openalex.org/keywords/list-decoding","display_name":"List decoding","score":0.5151723623275757},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.503786027431488},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.4796352982521057},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.4700644910335541},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4694478213787079},{"id":"https://openalex.org/keywords/q-learning","display_name":"Q-learning","score":0.4613068401813507},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4586155414581299},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.43236085772514343},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.41404345631599426},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.30429500341415405},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15821808576583862},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.124796062707901},{"id":"https://openalex.org/keywords/concatenated-error-correction-code","display_name":"Concatenated error correction code","score":0.11280515789985657},{"id":"https://openalex.org/keywords/block-code","display_name":"Block code","score":0.07948976755142212}],"concepts":[{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.8678920865058899},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.8673495650291443},{"id":"https://openalex.org/C106189395","wikidata":"https://www.wikidata.org/wiki/Q176789","display_name":"Markov decision process","level":3,"score":0.7708566784858704},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7298948168754578},{"id":"https://openalex.org/C193969084","wikidata":"https://www.wikidata.org/wiki/Q7452500","display_name":"Sequential decoding","level":4,"score":0.7138395309448242},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.5486149191856384},{"id":"https://openalex.org/C204397858","wikidata":"https://www.wikidata.org/wiki/Q4437907","display_name":"List decoding","level":5,"score":0.5151723623275757},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.503786027431488},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.4796352982521057},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.4700644910335541},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4694478213787079},{"id":"https://openalex.org/C188116033","wikidata":"https://www.wikidata.org/wiki/Q2664563","display_name":"Q-learning","level":3,"score":0.4613068401813507},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4586155414581299},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.43236085772514343},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.41404345631599426},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.30429500341415405},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15821808576583862},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.124796062707901},{"id":"https://openalex.org/C78944582","wikidata":"https://www.wikidata.org/wiki/Q5158264","display_name":"Concatenated error correction code","level":4,"score":0.11280515789985657},{"id":"https://openalex.org/C157125643","wikidata":"https://www.wikidata.org/wiki/Q884707","display_name":"Block code","level":3,"score":0.07948976755142212},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wcncw49093.2021.9420004","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wcncw49093.2021.9420004","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE Wireless Communications and Networking Conference Workshops (WCNCW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.7300000190734863,"display_name":"Peace, Justice and strong institutions"}],"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":23,"referenced_works":["https://openalex.org/W1757796397","https://openalex.org/W2033234285","https://openalex.org/W2091121840","https://openalex.org/W2106045225","https://openalex.org/W2121863487","https://openalex.org/W2145339207","https://openalex.org/W2148076418","https://openalex.org/W2150498905","https://openalex.org/W2161084929","https://openalex.org/W2257979135","https://openalex.org/W2271840356","https://openalex.org/W2949164659","https://openalex.org/W3011120880","https://openalex.org/W3099197037","https://openalex.org/W3100717665","https://openalex.org/W3130968093","https://openalex.org/W4214717370","https://openalex.org/W4287642324","https://openalex.org/W4298857966","https://openalex.org/W6637967152","https://openalex.org/W6694517276","https://openalex.org/W6775686901","https://openalex.org/W6784337479"],"related_works":["https://openalex.org/W2808418668","https://openalex.org/W4205451769","https://openalex.org/W1599365967","https://openalex.org/W3102491039","https://openalex.org/W2028976748","https://openalex.org/W3017203753","https://openalex.org/W2983681086","https://openalex.org/W2348545647","https://openalex.org/W2385322349","https://openalex.org/W2144918607"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"reinforcement":[3],"learning":[4,64],"(RL)":[5],"is":[6,60],"applied":[7],"to":[8,21,26,37,101],"find":[9],"effective":[10],"decoding":[11,25,94,104,107],"strategies":[12],"for":[13,62],"short":[14],"polar":[15],"codes.":[16],"We":[17],"first":[18],"illustrate":[19],"how":[20],"map":[22],"the":[23,34,39,43,49,52,77,91],"step-decision":[24],"a":[27],"Markov":[28],"decision":[29,67],"process.":[30],"Then,":[31],"we":[32],"choose":[33],"signal":[35],"reliability":[36],"formulate":[38],"reward":[40],"strategy,":[41],"and":[42,73,84,105],"path":[44],"metrics":[45],"are":[46],"taken":[47],"as":[48],"Q-values":[50],"of":[51,65],"state-action":[53],"pairs.":[54],"Finally,":[55],"an":[56],"adaptive":[57,78,96],"Q-table":[58,79,97],"approach":[59],"proposed":[61,92],"data-driven":[63],"optimal":[66],"strategies.":[68],"Compared":[69],"with":[70,95,108],"conventional":[71],"Q-learning":[72,75],"deep":[74],"networks,":[76],"results":[80,88],"in":[81],"low":[82,109],"computational":[83],"storage":[85],"complexity.":[86,110],"Simulation":[87],"show":[89],"that":[90],"RL":[93],"achieves":[98],"comparable":[99],"performance":[100],"learned":[102],"bit-flipping":[103],"SC":[106]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
