{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00008202008,0.0002026863,0.0002446013,0.0003038901,0.0001107086,0.00003421439,0.00005170772,0.00005683567,0.00002510749],"category_scores_gemma":[7.786571e-7,0.0002001867,0.00004088107,0.0003728907,0.00002723202,0.0002341626,0.000001670446,0.0002309838,0.00002207568],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001046078,"about_ca_system_score_gemma":0.000005251886,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005245012,"about_ca_topic_score_gemma":0.00002400533,"domain_scores_codex":[0.9990333,0.00002682928,0.0002854934,0.0002851162,0.0001103336,0.0002589091],"domain_scores_gemma":[0.9996458,0.00007380831,0.00003920261,0.0001375921,0.00003490209,0.00006869471],"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":[0.000008657405,0.00003736906,0.0003091769,0.00003588226,0.0001040485,0.000001197231,0.000888964,0.9782736,0.0002592416,1.507311e-7,1.363877e-7,0.02008153],"study_design_scores_gemma":[0.0007247818,0.00006416305,0.0001073894,0.0001225689,0.00009335826,0.000004068473,0.0006229213,0.9964542,0.001578326,0.000001416055,6.693924e-7,0.0002261336],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4474095,0.00007066752,0.5519846,0.000001235234,0.0000360977,0.000379173,0.000003390191,0.00007665914,0.00003861983],"genre_scores_gemma":[0.9857266,0.00009045214,0.01392671,0.000008543382,0.00001724244,0.0001715124,0.00000592178,0.00003635977,0.00001665232],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5383171,"threshold_uncertainty_score":0.8163376,"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."}}