{"id":"W3208817945","doi":"10.1109/lcomm.2021.3124902","title":"QoS-Aware Secrecy Rate Maximization in Untrusted NOMA With Trusted Relay","year":2021,"lang":"en","type":"article","venue":"IEEE Communications Letters","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"","keywords":"Computer science; Relay; Computer network; Quality of service; Maximization; Secrecy; Noma; Bottleneck; Transmitter power output; Power (physics); Telecommunications link; Mathematical optimization; Computer security; Mathematics; Transmitter; Embedded system","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":[0.002153751,0.001904476,0.001895648,0.0006441198,0.0009858514,0.002471803,0.001028941,0.001364185,0.001343958],"category_scores_gemma":[0.006340796,0.0007728935,0.0008506601,0.001108609,0.002425843,0.002373135,0.002176768,0.001439954,0.0006675371],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001353974,"about_ca_system_score_gemma":0.001266545,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001620549,"about_ca_topic_score_gemma":0.001267039,"domain_scores_codex":[0.9976173,0.001177958,0.00009161112,0.0003408495,0.0004045792,0.000367707],"domain_scores_gemma":[0.9962627,0.002331077,0.0004794686,0.0003082732,0.0004668318,0.0001516327],"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":[0.0003310721,0.00004161596,0.0005090923,0.000254314,0.00007703542,0.001038316,0.0002959012,0.902035,0.01416804,0.06933203,0.0009677287,0.01094989],"study_design_scores_gemma":[0.00002056104,0.00006016544,0.00007904173,0.00001613673,0.00001696672,0.0001987585,0.00006268871,0.9839352,0.002547906,0.012673,0.0003693666,0.00002013371],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07901675,0.001267546,0.9109792,0.0005660405,0.00009991255,0.0000596617,0.0001498039,0.0001806424,0.007680514],"genre_scores_gemma":[0.9726394,0.0007856608,0.02449981,0.00006111585,0.00008230376,0.00005342498,0.00003601076,0.00003301987,0.001809299],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002471803,"threshold_uncertainty_score":0.01139027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01650635925615672,"score_gpt":0.2239467702172368,"score_spread":0.2074404109610801,"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."}}