{"id":"W2785422296","doi":"10.1109/pimrc.2017.8292400","title":"On the user association and resource allocation in hetnets with mmWave base stations","year":2017,"lang":"en","type":"article","venue":"","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Base station; Heterogeneous network; Computer science; Resource allocation; Computer network; Heuristic; Computational complexity theory; Resource management (computing); Optimization problem; Distributed computing; Algorithm; Wireless; Telecommunications; Wireless network","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":[0.001144315,0.0009458002,0.001284739,0.0005486303,0.000719158,0.001093316,0.0009170352,0.0009702967,0.001763267],"category_scores_gemma":[0.002291253,0.0005740353,0.0005772801,0.001499633,0.001034123,0.001309501,0.001217709,0.0008885162,0.0003202894],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008347768,"about_ca_system_score_gemma":0.001105978,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004248731,"about_ca_topic_score_gemma":0.005242849,"domain_scores_codex":[0.9991859,0.0004697862,0.00002001411,0.00011491,0.00009877067,0.0001106529],"domain_scores_gemma":[0.9987924,0.0009505666,0.00009036933,0.00005337672,0.00007027501,0.0000430507],"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":[0.00008577166,0.00006981411,0.0004945965,0.0001021723,0.00004640884,0.0001028124,0.00005677834,0.9397922,0.001600224,0.02478562,0.001275389,0.03158824],"study_design_scores_gemma":[0.00000825506,0.00003581655,0.0001352386,0.000007190592,0.00001164187,0.00004300475,0.00002408313,0.9918283,0.0004158188,0.006809172,0.0006743363,0.000007103376],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0312998,0.001522712,0.9604909,0.0003624166,0.00007352156,0.00007547474,0.0000679667,0.00005915996,0.006048001],"genre_scores_gemma":[0.7296875,0.003853755,0.2590663,0.0002458244,0.0002167523,0.0002873734,0.0001412785,0.00005597258,0.006445072],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004248731,"threshold_uncertainty_score":0.008448005,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02015712087983334,"score_gpt":0.219480111068667,"score_spread":0.1993229901888336,"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."}}