{"id":"W2889214145","doi":"10.1109/tcc.2018.2867224","title":"User Association in Cloud RANs with Massive MIMO","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Cloud Computing","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Computer science; Cloud computing; Remote radio head; Optimization problem; Convex optimization; Resource allocation; Base station; Radio access network; Mathematical optimization; User equipment; Transmitter power output; Throughput; Computer network; Distributed computing; Regular polygon; Algorithm; Mathematics; Wireless; Mobile station; 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":[0.001006222,0.001190806,0.001426627,0.0003185014,0.0006747694,0.001409752,0.001506412,0.001198438,0.001738406],"category_scores_gemma":[0.002382664,0.0007435416,0.0006826479,0.000949408,0.001003705,0.00129801,0.001828006,0.001209467,0.0006434286],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007664918,"about_ca_system_score_gemma":0.001117072,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01106579,"about_ca_topic_score_gemma":0.009179419,"domain_scores_codex":[0.9989024,0.0003291331,0.00002413897,0.0002357726,0.0002158711,0.0002926112],"domain_scores_gemma":[0.9986877,0.0006204934,0.0002045836,0.0001559628,0.0001907948,0.0001404619],"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":[0.0001577912,0.00005056601,0.001562961,0.00004541288,0.00004583331,0.0004000286,0.00004682688,0.970706,0.001525747,0.006977131,0.001347136,0.01713455],"study_design_scores_gemma":[0.00000346428,0.00001276762,0.0001225894,0.000002022544,0.000003483957,0.00002954494,0.00001162388,0.9984239,0.0002064413,0.001023336,0.0001570719,0.000003804187],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07312839,0.0007349283,0.918852,0.0003415947,0.0001520895,0.00007004511,0.0001703073,0.0004250207,0.006125592],"genre_scores_gemma":[0.9096724,0.0003924749,0.08411758,0.0002250954,0.0001088228,0.00006694376,0.0001900973,0.0000539072,0.00517269],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01106579,"threshold_uncertainty_score":0.02200276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007686653918441501,"score_gpt":0.2202210035639929,"score_spread":0.2125343496455514,"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."}}