{"id":"W2993963137","doi":"10.1109/lwc.2019.2956702","title":"Joint Placement Design, Admission Control, and Power Allocation for NOMA-Based UAV Systems","year":2019,"lang":"en","type":"article","venue":"IEEE Wireless Communications Letters","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Mathematical optimization; Computer science; Convexity; Noma; Quality of service; Admission control; Optimization problem; Power (physics); Power control; Joint (building); Computational complexity theory; Convex optimization; Regular polygon; Computer network; Mathematics; Algorithm; Telecommunications link; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002560116,0.0001564762,0.0001836695,0.0001190121,0.0001680624,0.00008344482,0.0002965685,0.00007510241,0.000008065618],"category_scores_gemma":[0.000007304425,0.0001639915,0.00004128416,0.0001382741,0.00004461038,0.0001328089,0.00002029189,0.0001072468,0.00002581474],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001231633,"about_ca_system_score_gemma":0.00002519767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001575482,"about_ca_topic_score_gemma":0.000003214082,"domain_scores_codex":[0.9991466,0.00007126362,0.0003162533,0.0001770286,0.0001105032,0.0001783442],"domain_scores_gemma":[0.9985058,0.0002187973,0.00008598767,0.001028342,0.00009042277,0.00007068205],"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":[0.00001914305,0.00004708573,0.0001318645,0.00007764964,0.00003962157,6.038805e-8,0.0001117164,0.8319958,0.1633154,0.0009405125,0.002768129,0.0005530305],"study_design_scores_gemma":[0.001086725,0.00003604808,0.0003228163,0.00007196485,0.00002870179,0.000001294022,0.00006343838,0.9909099,0.002789945,0.000006452939,0.004478243,0.0002044909],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09336034,0.0003629094,0.9015471,0.002502677,0.000185124,0.001670329,0.0000244219,0.000207741,0.0001393987],"genre_scores_gemma":[0.9764237,0.00009332554,0.02195985,0.0004385001,0.00001954942,0.0008852923,0.0001057084,0.00004412005,0.00002993257],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8830634,"threshold_uncertainty_score":0.6687378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01861230802942663,"score_gpt":0.2219544249569995,"score_spread":0.2033421169275729,"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."}}