{"id":"W3014401415","doi":"10.1109/jiot.2020.2985424","title":"Multicell Edge Coverage Enhancement Using Mobile UAV-Relay","year":2020,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Natural Science Foundation of Jiangsu Province for Distinguished Young Scholars; Fundamental Research Funds for the Central Universities; Natural Science Foundation of Jiangsu Province; Government of Jiangsu Province; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China; Royal Academy of Engineering","keywords":"Base station; Benchmark (surveying); Enhanced Data Rates for GSM Evolution; Wireless; Iterative method; Mobile edge computing; Quality of service; Transmission (telecommunications); Convex optimization","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":[0.0003344332,0.0009119831,0.0006143504,0.0004869467,0.0003848591,0.0006182922,0.0008521593,0.0005758047,0.001128767],"category_scores_gemma":[0.0009520883,0.0001935633,0.0004290906,0.0005576398,0.0003064221,0.000912996,0.001104502,0.0004125526,0.0002214221],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006174449,"about_ca_system_score_gemma":0.0003800832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003692299,"about_ca_topic_score_gemma":0.004638587,"domain_scores_codex":[0.9996976,0.00008858889,0.000008681707,0.0000534978,0.0000681091,0.00008356386],"domain_scores_gemma":[0.9996068,0.0001821316,0.00006866206,0.00004467125,0.00005843713,0.00003946226],"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":[0.0002835746,0.0001122911,0.001215105,0.0001416098,0.00006889877,0.0004765843,0.0001470243,0.883137,0.02897613,0.008259091,0.001771122,0.07541146],"study_design_scores_gemma":[0.00001262218,0.00008526183,0.0001602121,0.000005614068,0.00002015074,0.0001125932,0.00003520232,0.9940646,0.003754934,0.00116169,0.0005790411,0.00000800116],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1719669,0.00192146,0.8157656,0.0002331042,0.00007048862,0.00006360013,0.00009403328,0.0006028918,0.009282044],"genre_scores_gemma":[0.9597112,0.0004722872,0.0383858,0.00005381407,0.00001716638,0.00002808911,0.00004385236,0.00002446755,0.001263376],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003692299,"threshold_uncertainty_score":0.007341623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01473869157419963,"score_gpt":0.2322080136468975,"score_spread":0.2174693220726979,"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."}}