{"id":"W2065439483","doi":"10.1109/tcomm.2004.836559","title":"Accurate Simulation of Multiple Cross-Correlated Rician Fading Channels","year":2004,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; Queen's University","funders":"","keywords":"Rician fading; Autocorrelation; Fading; Computer science; Rayleigh fading; Fading distribution; Autoregressive model; Channel (broadcasting); Algorithm; Channel state information; Wireless; Electronic engineering; Mathematics; Statistics; Telecommunications; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001222903,0.0001928593,0.0002110956,0.0002962323,0.0003806479,0.00003390985,0.0009006474,0.0001491499,0.00002149811],"category_scores_gemma":[0.00002071325,0.000230186,0.0001146677,0.0006547686,0.00018632,0.0004456709,0.000008204979,0.0005121041,0.00004398206],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002108313,"about_ca_system_score_gemma":0.00002638296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005515512,"about_ca_topic_score_gemma":0.00008703,"domain_scores_codex":[0.9989279,0.00005751828,0.0005206194,0.0001467067,0.0001458114,0.0002014603],"domain_scores_gemma":[0.997135,0.0004600079,0.0001169806,0.002041526,0.0001818791,0.00006455365],"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":[0.000008132857,0.0001403448,0.000009074932,0.00001469548,0.00003715821,1.484529e-7,0.0005340126,0.9866168,0.00557128,0.0003518147,0.00000284405,0.006713657],"study_design_scores_gemma":[0.0006333597,0.00004267419,0.0001372157,0.0001338942,0.00002498618,0.000002297155,0.00007687043,0.8552718,0.1410581,0.001465635,0.0008848484,0.000268411],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0204658,0.0002273843,0.9759887,0.0001317994,0.0002048542,0.0003680044,0.0000544805,0.001125121,0.001433897],"genre_scores_gemma":[0.9824228,0.0009261095,0.01632026,0.00002464633,0.000008298029,0.0001602658,0.00002637843,0.00005938464,0.00005186126],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.961957,"threshold_uncertainty_score":0.9386711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04097646254708521,"score_gpt":0.3210827001431497,"score_spread":0.2801062375960645,"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."}}