{"id":"W3108119177","doi":"10.1109/ccece47787.2020.9255673","title":"Turbo Receiver for Polar-Coded OFDM systems with unknown CSI","year":2020,"lang":"en","type":"article","venue":"","topic":"Error Correcting Code Techniques","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Computer science; Orthogonal frequency-division multiplexing; Fading; Turbo code; Turbo; Decoding methods; Channel state information; Algorithm; Bit error rate; Turbo equalizer; Radio receiver design; Detector; Electronic engineering; Channel (broadcasting); Telecommunications; Concatenated error correction code; Wireless; Engineering; Block code","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":[0.0007739976,0.0004927581,0.0004662299,0.0003824439,0.000434789,0.0006634418,0.00054368,0.0009210627,0.001218454],"category_scores_gemma":[0.002739007,0.0002306995,0.0003458041,0.0004703709,0.0005711222,0.0008919677,0.000511188,0.0008796305,0.000879965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003522473,"about_ca_system_score_gemma":0.000923889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009386766,"about_ca_topic_score_gemma":0.001312351,"domain_scores_codex":[0.9994105,0.0001971909,0.00002572241,0.00006544998,0.000244308,0.00005679922],"domain_scores_gemma":[0.9988219,0.0005101468,0.0001010671,0.0001114079,0.0004248214,0.00003055064],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0007704849,0.00007407413,0.002420548,0.0006032815,0.0002057263,0.001108148,0.0004553137,0.3884887,0.09316667,0.1462412,0.005263971,0.3612018],"study_design_scores_gemma":[0.00002311866,0.0001711522,0.0002358769,0.00003452536,0.00006389503,0.0007545677,0.00003605297,0.9541802,0.03039605,0.007688928,0.006362511,0.00005306043],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01003145,0.0006138989,0.986111,0.0001605343,0.0000817273,0.00001785734,0.00002624837,0.0002416008,0.002715734],"genre_scores_gemma":[0.595513,0.001864583,0.393768,0.0003244844,0.0001855414,0.00006841897,0.0001252442,0.00005423883,0.008096457],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001218454,"threshold_uncertainty_score":0.004093349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02702158799140332,"score_gpt":0.2394120385355479,"score_spread":0.2123904505441445,"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."}}