{"id":"W2040714707","doi":"10.1109/tmc.2013.36","title":"Two-Tier HetNets with Cognitive Femtocells: Downlink Performance Modeling and Analysis in a Multichannel Environment","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Mobile Computing","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":154,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Femtocell; Heterogeneous network; Computer science; Femto-; Macro; Stochastic geometry; Interference (communication); Computer network; Telecommunications link; Macrocell; Cognitive radio; LTE Advanced; Base station; Rayleigh fading; Transmission (telecommunications); Wireless; Fading; Wireless network; Telecommunications; Channel (broadcasting)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006989904,0.001012983,0.0005911218,0.0004011547,0.0003981874,0.001080268,0.0007262069,0.0009495495,0.0004890253],"category_scores_gemma":[0.001235604,0.0003894702,0.000580553,0.0004568353,0.0009619353,0.0008790381,0.0008017768,0.0004681261,0.0001961688],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009303883,"about_ca_system_score_gemma":0.000550118,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009387224,"about_ca_topic_score_gemma":0.006509041,"domain_scores_codex":[0.9995027,0.0001827755,0.00001195531,0.00006077698,0.0001006152,0.0001413148],"domain_scores_gemma":[0.9992993,0.0003237976,0.0001207755,0.00006076218,0.0001430488,0.00005232875],"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":[0.00003684583,0.00002520744,0.001263321,0.00001312695,0.00002050183,0.0001294546,0.00003773352,0.9896813,0.002115727,0.004750394,0.000142802,0.001783627],"study_design_scores_gemma":[0.000001416338,0.00001758188,0.0003030627,0.000001444664,0.000004879194,0.00002431479,0.00001365399,0.9986699,0.0002326367,0.0006766449,0.00004976844,0.000004713934],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4685225,0.0008754887,0.5184852,0.0003127848,0.00006715009,0.00005433149,0.0002200933,0.0002549215,0.01120746],"genre_scores_gemma":[0.9923149,0.0002653463,0.006342392,0.0000412482,0.00002062417,0.00001830329,0.00003157347,0.00001116044,0.0009544954],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009387224,"threshold_uncertainty_score":0.01866519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00782092328080329,"score_gpt":0.2028059329538449,"score_spread":0.1949850096730417,"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."}}