{"id":"W4200197391","doi":"10.1109/wcsp52459.2021.9613552","title":"UAV-aided Secure NOMA Transmission via Trajectory and Resource Optimization","year":2021,"lang":"en","type":"article","venue":"2021 13th International Conference on Wireless Communications and Signal Processing (WCSP)","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"","keywords":"Computer science; Jamming; Telecommunications link; Noma; Transmission (telecommunications); Scheduling (production processes); Resource allocation; Transmitter power output; Trajectory; Optimization problem; Mathematical optimization; Convex optimization; Computer network; Trajectory optimization; Power (physics); Real-time computing; Regular polygon; Transmitter; Algorithm; Telecommunications; Mathematics; 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":[0.0005299192,0.0009928955,0.0007735235,0.0003941576,0.0005307298,0.0006962771,0.000574005,0.0006525982,0.001210121],"category_scores_gemma":[0.001332226,0.0003381163,0.0005689757,0.0007195447,0.0006571389,0.0007839862,0.0009712578,0.0007489317,0.0003857156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007223502,"about_ca_system_score_gemma":0.001125237,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003231254,"about_ca_topic_score_gemma":0.002809297,"domain_scores_codex":[0.9996038,0.0001331859,0.00001645278,0.00006377823,0.0001027403,0.00008012546],"domain_scores_gemma":[0.9995252,0.0002482664,0.00008848016,0.0000441427,0.00006831409,0.000025556],"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":[0.00005764619,0.00002038084,0.0002306386,0.0000382019,0.00001774408,0.00007918819,0.00004695953,0.9708506,0.002874811,0.01047515,0.0005791154,0.0147294],"study_design_scores_gemma":[0.000004873428,0.0000195783,0.00003984906,0.00000236921,0.000002690849,0.00001850358,0.000008013696,0.9976961,0.0004628207,0.001527991,0.0002138799,0.000003250781],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02176154,0.0003529218,0.9735545,0.000177636,0.00003996812,0.00003800072,0.0000519993,0.0001793164,0.003844164],"genre_scores_gemma":[0.8733976,0.0004518898,0.1218152,0.00007165704,0.00004838802,0.0001534548,0.000131362,0.00004345233,0.003886938],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003231254,"threshold_uncertainty_score":0.006424904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0227551995539269,"score_gpt":0.2520968779955975,"score_spread":0.2293416784416706,"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."}}