{"id":"W2786668272","doi":"10.1109/pimrc.2017.8292618","title":"Unified stochastic geometry analysis of downlink cellular networks","year":2017,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; University of Toronto","funders":"","keywords":"Rician fading; Stochastic geometry; Fading; Nakagami distribution; Moment-generating function; Computer science; Cumulative distribution function; Rayleigh fading; Signal-to-interference-plus-noise ratio; Fading distribution; Telecommunications link; Weibull fading; Interference (communication); Algorithm; Signal-to-noise ratio (imaging); Topology (electrical circuits); Mathematics; Telecommunications; Probability density function; Statistics; Channel (broadcasting); Physics","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":[0.0007822429,0.001004785,0.0008870207,0.001359096,0.0004411194,0.001604805,0.0008134553,0.000698469,0.00191701],"category_scores_gemma":[0.002636036,0.0003829302,0.0007864555,0.0008714105,0.0009367285,0.001073314,0.001170124,0.0008474959,0.0003939263],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002469279,"about_ca_system_score_gemma":0.0009897448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01193039,"about_ca_topic_score_gemma":0.005732344,"domain_scores_codex":[0.9993839,0.0002642925,0.00001798849,0.00005998118,0.0001725394,0.0001012419],"domain_scores_gemma":[0.9989512,0.000490643,0.0001504918,0.00007144732,0.0002558722,0.00008029109],"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":[0.00001565198,0.00001122272,0.0008250899,0.00003270061,0.0000270172,0.0001131235,0.00004521885,0.7492201,0.0008352626,0.243815,0.001699975,0.003359725],"study_design_scores_gemma":[0.000002492813,0.000008633234,0.0002766077,0.000007250006,0.000005286744,0.00002739408,0.00001935228,0.9687119,0.00008596702,0.02992852,0.0009201869,0.000006486424],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06976978,0.003344569,0.8885711,0.001876198,0.0001727481,0.00007283307,0.000878076,0.0002227885,0.03509184],"genre_scores_gemma":[0.9686725,0.003640564,0.01790783,0.0002518535,0.0002783418,0.0001321384,0.0005078053,0.00008143172,0.008527573],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01193039,"threshold_uncertainty_score":0.02372193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009608151393132256,"score_gpt":0.2237415706172437,"score_spread":0.2141334192241114,"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."}}