{"doi":"10.1109/iwcmc.2018.8450424","title":"Big Data Viewpoint On Channel Information Measures Based on ACE Algorithm","abstract":null,"journal":"2018 14th International Wireless Communications & Mobile Computing Conference (IWCMC)","year":2018,"id":616705,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1590100,"name":"Rui She","orcid":null,"position":1,"is_corresponding":false},{"id":1590104,"name":"Jiaxun Lu","orcid":null,"position":2,"is_corresponding":false},{"id":137736,"name":"Pingyi Fan","orcid":"0000-0002-0658-6079","position":3,"is_corresponding":false},{"id":1590096,"name":"Shanyun Liu","orcid":null,"position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Big Data Viewpoint On Channel Information Measures Based on ACE Algorithm","abstract":"In this paper, we focus on the mutual information, which can characterize the transmission ability because it shows correlation between channel input and channel output. Shannon entropy and mutual information are the cornerstones of information theory. In addition, Chernoff information is another fundamental channel information measure, and it describe the maximum achievable exponent of the error probability in hypothesis testing. Uased on alternating conditional expectation (ACE) algorithm, we decompose these two mutual information. In fact, their decomposition results are similar in big data prespective. In this sense, these two kinds of mutual information are just different measures of the same information quantity. This paper also deduces that the channel performance only depends on channel parameters and the decomposition results of a new proposed mutual information should agree with the impact of the parameters.","is_dataset_classified":null,"base_score":0.0,"endowment":0.0,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"19767382","pmcid":null,"openalex_id":"https://openalex.org/W2889544313","authors":[],"funders":[],"total_grants":0,"fwci":0.0,"citation_percentile":0.10131624,"influential_citations":0,"citation_trend":[],"oa_status":"closed","license":null,"oa_locations":[{"url":"http://xplorestaging.ieee.org/ielx7/8410977/8450266/08450424.pdf?arnumber=8450424","host_type":"publisher"},{"url":"https://doi.org/10.1109/iwcmc.2018.8450424","host_type":""}],"fields_of_study":["Wireless Communication Security Techniques","Distributed Sensor Networks and Detection Algorithms","Blind Source Separation Techniques"],"mesh_terms":[],"keywords":["Mutual information","Entropy (arrow of time)","Conditional mutual information","Information theory","Channel (broadcasting)","Computer science","Conditional entropy","Total correlation","Algorithm","Measure (data warehouse)","Channel capacity","Mathematics","Data mining","Artificial intelligence","Statistics","Principle of maximum entropy"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-02T23:35:53.474563Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}