{"id":"W3206067486","doi":"10.1109/twc.2021.3120268","title":"Joint User Grouping and Power Optimization for Secure mmWave-NOMA Systems","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Fundamental Research Funds for the Central Universities; National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Computer science; Computer network; Noma; Precoding; Wireless network; Artificial noise; Secrecy; Wireless; Optimization problem; Channel (broadcasting); Interference (communication); MIMO; Transmitter; Algorithm; Telecommunications; Telecommunications link; Computer security","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":[0.0009001421,0.001485337,0.00125349,0.0004110906,0.0007259844,0.0009293102,0.000835941,0.00081304,0.001269662],"category_scores_gemma":[0.001399897,0.0004610052,0.0006739945,0.0009978452,0.0008707867,0.0008891281,0.001211786,0.0008170996,0.0004638143],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008288693,"about_ca_system_score_gemma":0.001022039,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003434957,"about_ca_topic_score_gemma":0.004126885,"domain_scores_codex":[0.9989115,0.000496533,0.00003584617,0.0001565517,0.0002237563,0.0001758271],"domain_scores_gemma":[0.999572,0.0001886778,0.00008657381,0.00005094166,0.00006415221,0.00003764009],"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":[0.0001395429,0.00006045918,0.000490982,0.00006340632,0.00004603183,0.0001528962,0.00009878528,0.9476193,0.003238721,0.0164015,0.001846805,0.02984159],"study_design_scores_gemma":[0.000007908633,0.00003712449,0.00008423503,0.000002849088,0.000006316808,0.00002271939,0.00001645455,0.9956524,0.0003387181,0.003441026,0.0003856266,0.000004685339],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01706313,0.0006729795,0.9788542,0.0002231688,0.00005786226,0.0000390409,0.00004156703,0.000129071,0.002918962],"genre_scores_gemma":[0.8696487,0.0007938734,0.1256648,0.0001688255,0.0001173875,0.0001605982,0.0000949445,0.00003980846,0.003311161],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003434957,"threshold_uncertainty_score":0.006829917,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02586600274619065,"score_gpt":0.2465552674133212,"score_spread":0.2206892646671306,"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."}}