{"id":"W2949201432","doi":"10.3390/electronics8060695","title":"PEP Analysis of AF Relay NOMA Systems Employing Order Statistics of Cascaded Channels","year":2019,"lang":"en","type":"article","venue":"Electronics","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Khalifa University of Science, Technology and Research; National Natural Science Foundation of China","keywords":"Noma; Relay; Pairwise error probability; Computer science; Interference (communication); Monte Carlo method; Higher-order statistics; Wireless; Bessel function; Channel (broadcasting); Single antenna interference cancellation; Pairwise comparison; Power (physics); Expression (computer science); Topology (electrical circuits); Electronic engineering; Algorithm; Mathematics; Fading; Telecommunications; Statistics; Engineering; Physics; Telecommunications link; Signal processing; Artificial intelligence","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":[0.001427051,0.0009796886,0.0006749536,0.0005745501,0.0003346491,0.0009408439,0.0005629612,0.0007194424,0.00125001],"category_scores_gemma":[0.003594118,0.0003743509,0.0006283165,0.0005724293,0.001008414,0.00117097,0.000747423,0.0007477357,0.000203858],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007916832,"about_ca_system_score_gemma":0.0007217567,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00172336,"about_ca_topic_score_gemma":0.00127172,"domain_scores_codex":[0.9993721,0.0002244737,0.00002867686,0.00007614097,0.0002038917,0.00009482115],"domain_scores_gemma":[0.9973168,0.00196103,0.0002310332,0.0001423933,0.0003049996,0.00004382838],"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":[0.0001011935,0.00002508312,0.001000703,0.0001033722,0.00004788674,0.0003293266,0.0000953053,0.9541054,0.007439559,0.03080787,0.0002223584,0.005722118],"study_design_scores_gemma":[0.000003184517,0.00003066061,0.0003377933,0.00000655024,0.00001042711,0.00009183672,0.00001444102,0.9941005,0.001252665,0.004045339,0.00009770683,0.000008806287],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1966338,0.001148713,0.7912987,0.0002043344,0.00004833837,0.00006991541,0.0001945378,0.0001605407,0.01024115],"genre_scores_gemma":[0.9782141,0.0006943516,0.01939306,0.00003983872,0.00003182757,0.00003525142,0.00006423843,0.00002144261,0.001505775],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00172336,"threshold_uncertainty_score":0.007547081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008758813332890511,"score_gpt":0.2337715543785304,"score_spread":0.2250127410456399,"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."}}