{"id":"W2276436981","doi":"10.1109/vtcfall.2015.7391157","title":"Stochastic Geometry Modeling of Cellular Uplink Power Control under Composite Rayleigh-Lognormal Fading","year":2015,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Path loss; Rayleigh fading; Shadow mapping; Stochastic geometry; Telecommunications link; Coverage probability; Log-distance path loss model; Log-normal distribution; Power control; Fading; Transmitter power output; Signal-to-interference-plus-noise ratio; Interference (communication); Computer science; Mathematics; Topology (electrical circuits); Algorithm; Power (physics); Statistics; Telecommunications; Physics; Wireless; Decoding methods; Transmitter; Channel (broadcasting)","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":[0.0006943521,0.0009037589,0.0007596402,0.0005245694,0.0003600924,0.0009842841,0.0009163119,0.0008174847,0.0008366785],"category_scores_gemma":[0.002290218,0.0004571904,0.0005141827,0.0004692709,0.001190509,0.000718254,0.0006144227,0.0005605451,0.0001951898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001649352,"about_ca_system_score_gemma":0.0007196263,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01487131,"about_ca_topic_score_gemma":0.007795637,"domain_scores_codex":[0.9993772,0.0001968304,0.00001737338,0.0001049064,0.0001556694,0.0001479936],"domain_scores_gemma":[0.9985535,0.0007487203,0.0002801853,0.00006395929,0.0002778321,0.00007578256],"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":[0.00001111223,0.000004014765,0.0002002602,0.000005229773,0.000004657832,0.00004059293,0.00001254525,0.9950635,0.0004932627,0.003477646,0.00006992176,0.0006173435],"study_design_scores_gemma":[0.000002026641,0.000009570214,0.0001159764,6.746222e-7,0.000002238477,0.000008554746,0.000004282694,0.9991528,0.00008568607,0.0005831817,0.00003255705,0.000002510794],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1938393,0.0006155713,0.7953905,0.00052543,0.00007188481,0.00006833591,0.0002078244,0.0002875988,0.008993587],"genre_scores_gemma":[0.9929214,0.0002433552,0.004855184,0.00002991341,0.00001821707,0.00003260807,0.00004121878,0.00001980403,0.001838329],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01487131,"threshold_uncertainty_score":0.02956951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01415143766765608,"score_gpt":0.2120569478774723,"score_spread":0.1979055102098163,"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."}}