{"id":"W2160829317","doi":"10.7840/kics.2013.38a.12.1125","title":"Distributed BS Transmit Power Control for Utility Maximization in Small-Cell Networks","year":2013,"lang":"en","type":"article","venue":"The Journal of Korean Institute of Communications and Information Sciences","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kootenay Association for Science & Technology","funders":"","keywords":"Throughput; Computer science; Enhanced Data Rates for GSM Evolution; Scheduling (production processes); Transmitter power output; Power control; Computer network; Base station; Femtocell; Distributed computing; Algorithm; Real-time computing; Power (physics); Mathematical optimization; Wireless; Mathematics; Telecommunications","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":[0.0007266804,0.0006623839,0.0006344281,0.0002469372,0.0003761895,0.0008877199,0.0007101244,0.0004918677,0.001611643],"category_scores_gemma":[0.001690555,0.0002153049,0.00029701,0.0004708451,0.0007156405,0.0006322709,0.0006360542,0.0006302906,0.0001839506],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001034454,"about_ca_system_score_gemma":0.0007691226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00401197,"about_ca_topic_score_gemma":0.003108986,"domain_scores_codex":[0.999632,0.0001408414,0.0000107089,0.00006331682,0.00009313524,0.00005986907],"domain_scores_gemma":[0.9994385,0.0003709208,0.00005201202,0.00002217504,0.00008680107,0.00002947647],"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":[0.00006629909,0.00003020655,0.0002296756,0.00004448683,0.00001374827,0.00003627822,0.00004490991,0.9756413,0.001743847,0.007889757,0.0005300135,0.01372949],"study_design_scores_gemma":[0.00000583856,0.00001326404,0.00003446205,0.000001173041,0.000002022646,0.000004184626,0.000006156666,0.9978387,0.0001919232,0.001796837,0.0001041482,0.000001347049],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02385521,0.0003952052,0.9711864,0.0002189712,0.00003876079,0.000049127,0.00002888603,0.0001655237,0.004061886],"genre_scores_gemma":[0.9578604,0.0004026751,0.03896014,0.0000728842,0.00004973979,0.00009642218,0.00003168022,0.00003284995,0.002493114],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00401197,"threshold_uncertainty_score":0.007977188,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01457992467441353,"score_gpt":0.2240184587932519,"score_spread":0.2094385341188383,"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."}}