{"id":"W2549535052","doi":"10.1186/s13638-016-0774-2","title":"Compressed sensing-based channel estimation for ACO-OFDM visible light communications in 5G systems","year":2016,"lang":"en","type":"article","venue":"EURASIP Journal on Wireless Communications and Networking","topic":"Optical Wireless Communication Technologies","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"National Research Foundation of Korea; Sejong University; National Research Foundation","keywords":"Visible light communication; Orthogonal frequency-division multiplexing; Computer science; Matching pursuit; Compressed sensing; Algorithm; Computational complexity theory; Bit error rate; Channel (broadcasting); Mean squared error; Noise power; Power (physics); Telecommunications; Mathematics; Statistics; Optics; Light-emitting diode","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003425776,0.0004460504,0.0003550993,0.0004171907,0.0003298586,0.0003766752,0.0005347198,0.0004893757,0.0009870647],"category_scores_gemma":[0.001438346,0.0001542296,0.0002482455,0.0005317301,0.0003680333,0.0007816156,0.0005164175,0.000724986,0.000233737],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000289931,"about_ca_system_score_gemma":0.0007501699,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002883503,"about_ca_topic_score_gemma":0.003804192,"domain_scores_codex":[0.9996488,0.00007446284,0.00001564006,0.0000565253,0.0001649869,0.0000396155],"domain_scores_gemma":[0.9995105,0.0002220052,0.00007191284,0.00005123856,0.0001222849,0.00002201508],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005083858,0.0001731981,0.002099982,0.0002126205,0.00007598009,0.0002754454,0.00016559,0.3872596,0.06449912,0.0222966,0.003579239,0.5188543],"study_design_scores_gemma":[0.000009534302,0.0000527972,0.000258826,0.000006282371,0.000006367728,0.000066471,0.00001722221,0.9921991,0.005313241,0.001236783,0.0008229404,0.00001039559],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01899422,0.0002837782,0.9786595,0.0002181579,0.00006704893,0.00003619903,0.00004649201,0.0001925167,0.00150209],"genre_scores_gemma":[0.6400853,0.000592272,0.3562372,0.0002174244,0.0001807122,0.0000959272,0.0002084997,0.00002858649,0.002354138],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002883503,"threshold_uncertainty_score":0.00573343,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04309532925918706,"score_gpt":0.2805977882766674,"score_spread":0.2375024590174803,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}