{"id":"W2168330593","doi":"10.1109/vtcf.2006.427","title":"An OFDM Rayleigh Fading Channel Simulator","year":2006,"lang":"en","type":"article","venue":"IEEE Vehicular Technology Conference","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Correlation function (quantum field theory); Rayleigh fading; Computer science; Fading; Algorithm; Orthogonal frequency-division multiplexing; Transformation (genetics); Correlation; Computation; Covariance matrix; Channel (broadcasting); Gaussian; Cross-correlation; Additive white Gaussian noise; Electronic engineering; Spectral density; Mathematics; Decoding methods; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004530423,0.0004872741,0.0005094881,0.0003945722,0.0002751487,0.0005313508,0.001149546,0.0007399364,0.006698427],"category_scores_gemma":[0.001585446,0.0002311937,0.0003979846,0.0006196682,0.0001807892,0.0006537988,0.000404803,0.0008607288,0.001171565],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004439671,"about_ca_system_score_gemma":0.0008271876,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003111707,"about_ca_topic_score_gemma":0.002688178,"domain_scores_codex":[0.9997459,0.0000848614,0.00001849144,0.00002854595,0.00008296376,0.00003923163],"domain_scores_gemma":[0.9993098,0.0002910142,0.00004487053,0.000133794,0.0001905264,0.00003002681],"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":[0.0001708534,0.000100786,0.001191005,0.0001219029,0.00005907784,0.0001599198,0.00005859586,0.9478884,0.00768631,0.0203564,0.005335633,0.01687109],"study_design_scores_gemma":[0.00003093248,0.0000330761,0.000120288,0.000003139008,0.000007087896,0.00003906523,0.000005288024,0.9924607,0.002359053,0.0009778191,0.003956988,0.000006534734],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1383457,0.0005037563,0.8227382,0.0005345141,0.0002369286,0.0006564237,0.006177039,0.01132108,0.01948625],"genre_scores_gemma":[0.7157412,0.001023137,0.2634238,0.0002868315,0.00006430716,0.0008005099,0.005251209,0.0005177827,0.01289111],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006698427,"threshold_uncertainty_score":0.02240849,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01054464313282745,"score_gpt":0.238541097823528,"score_spread":0.2279964546907006,"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."}}