{"id":"W2160956890","doi":"10.1109/cnsr.2005.52","title":"Rayleigh Flat Fading Channels&amp;#146; Capacity","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":50,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Rayleigh fading; Fading; Fading distribution; Channel state information; Additive white Gaussian noise; Channel capacity; Channel (broadcasting); Independent and identically distributed random variables; Computer science; Rayleigh scattering; Transmission (telecommunications); Mathematics; Telecommunications; Topology (electrical circuits); Statistics; Electronic engineering; Random variable; Physics; Engineering; Wireless; Combinatorics; Optics","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":[0.0005906046,0.0007144235,0.0006916925,0.0004666439,0.0004400795,0.001128902,0.0007494551,0.0005921081,0.003387104],"category_scores_gemma":[0.003495088,0.0001707614,0.0002948354,0.001014365,0.001172796,0.001464933,0.0006041949,0.0005607202,0.0005885429],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001049652,"about_ca_system_score_gemma":0.001067135,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007392458,"about_ca_topic_score_gemma":0.002605941,"domain_scores_codex":[0.9992105,0.0002138973,0.00001771722,0.0001020201,0.0002296489,0.0002262242],"domain_scores_gemma":[0.9985164,0.0008720512,0.0001242653,0.0001519083,0.0003041203,0.00003132137],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002857972,0.00001290946,0.0002882466,0.00009722262,0.00001289382,0.0001783002,0.00004717863,0.8970768,0.001947541,0.09038234,0.00187775,0.008050252],"study_design_scores_gemma":[0.000005084149,0.00001683538,0.0002653461,0.00002349837,0.00001048026,0.0001223987,0.00003053353,0.9740253,0.0008164762,0.02271527,0.001952905,0.00001584994],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1259295,0.006737378,0.7869065,0.001026449,0.0002619859,0.00009798269,0.001351541,0.0006793342,0.07700928],"genre_scores_gemma":[0.9726762,0.003169762,0.01806335,0.0001290154,0.0001363284,0.0001168022,0.0001971436,0.00005515145,0.005456307],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007392458,"threshold_uncertainty_score":0.01469886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0177663602656419,"score_gpt":0.2107839778143332,"score_spread":0.1930176175486913,"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."}}