{"id":"W2343651235","doi":"10.1109/tvt.2016.2518988","title":"Underlay Interference Analysis of Power Control and Receiver Association Schemes","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Cognitive Radio Networks and Spectrum Sensing","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Transmitter; Underlay; Rayleigh fading; Transmitter power output; Power control; Path loss; Cognitive radio; Fading; Node (physics); Interference (communication); Computer science; Electronic engineering; Topology (electrical circuits); Mathematics; Telecommunications; Engineering; Power (physics); Electrical engineering; Signal-to-noise ratio (imaging); Wireless; Physics; 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":[0.001600572,0.0008735496,0.0009056312,0.0005987632,0.0004692878,0.001211156,0.001179243,0.000683674,0.001755675],"category_scores_gemma":[0.006006274,0.0003612622,0.0006973057,0.0008146173,0.0011116,0.001966379,0.001270501,0.0009283685,0.0002547525],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001222168,"about_ca_system_score_gemma":0.0007358908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001713351,"about_ca_topic_score_gemma":0.0009794137,"domain_scores_codex":[0.9983488,0.0004248211,0.00005330719,0.0002384422,0.0005985964,0.000336006],"domain_scores_gemma":[0.9965968,0.002010503,0.0004915633,0.0003519071,0.0004751854,0.00007404325],"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":[0.0001187034,0.0000533425,0.001321387,0.0001032116,0.00008987021,0.0002273412,0.0001987889,0.9058132,0.006777307,0.06449792,0.0003835284,0.02041547],"study_design_scores_gemma":[0.000005821276,0.0000523406,0.0006281027,0.000008580222,0.00002507859,0.0001159219,0.00003774172,0.988514,0.001319138,0.008904183,0.0003797729,0.000009299606],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1936484,0.001999934,0.7901568,0.0001498192,0.00003978621,0.00004121391,0.00008851335,0.0001447505,0.01373075],"genre_scores_gemma":[0.9833239,0.0006259509,0.01391892,0.00005462122,0.00005994884,0.00003423048,0.00003981619,0.00002732081,0.001915359],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001755675,"threshold_uncertainty_score":0.008867443,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006530382434360853,"score_gpt":0.216410318083249,"score_spread":0.2098799356488881,"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."}}