{"id":"W2061248445","doi":"10.1145/1582379.1582542","title":"Channel estimation and performance of BICM-ID with signal space diversity over time-correlated Rayleigh fading channels","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"","keywords":"Fading; Computer science; Channel (broadcasting); Channel state information; Algorithm; Rayleigh fading; Decoding methods; Estimator; Diversity gain; Bit error rate; Telecommunications; Wireless; Mathematics; Statistics","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":[0.0020752,0.0007910772,0.0008236042,0.0007737715,0.0004925963,0.0007602134,0.0005800613,0.0008869683,0.0006126871],"category_scores_gemma":[0.01084828,0.0003187337,0.0002066499,0.0007818972,0.0009861656,0.0009315006,0.001397263,0.0005817877,0.0001903494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006340182,"about_ca_system_score_gemma":0.00128114,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005153716,"about_ca_topic_score_gemma":0.003203895,"domain_scores_codex":[0.9985464,0.000629898,0.00005468734,0.0001088708,0.0003843808,0.0002757279],"domain_scores_gemma":[0.9937699,0.004037298,0.0004409829,0.0004817505,0.001153032,0.0001170769],"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":[0.001157454,0.00008604741,0.007650164,0.0001778374,0.00008880501,0.0002268412,0.0002298781,0.9220138,0.01082226,0.007373719,0.000603064,0.04957016],"study_design_scores_gemma":[0.00002735163,0.0001356285,0.001503695,0.00001495694,0.00002333563,0.0001500557,0.00004682149,0.9877959,0.0089232,0.001219563,0.0001293764,0.00003004092],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7001196,0.001213902,0.2920069,0.0003136463,0.00005027655,0.00004379982,0.0001557924,0.0005790776,0.005516967],"genre_scores_gemma":[0.9845467,0.0001645155,0.01470697,0.00002927939,0.00001082232,0.00001643028,0.00007627179,0.00001072726,0.0004382177],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005153716,"threshold_uncertainty_score":0.01097482,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006453129286778251,"score_gpt":0.1947950887869466,"score_spread":0.1883419595001684,"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."}}