{"id":"W2947459282","doi":"10.1109/tvt.2019.2920144","title":"Secure Transmission via Joint Precoding Optimization for Downlink MISO NOMA","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Engineering and Physical Sciences Research Council","keywords":"Precoding; Eavesdropping; Telecommunications link; Computer science; Transmitter power output; Zero-forcing precoding; Channel state information; Base station; Computer network; Secure transmission; Optimization problem; Transmission (telecommunications); Convex optimization; Channel (broadcasting); Wireless; Transmitter; Encryption; Telecommunications; MIMO; Algorithm; Mathematics; Regular polygon","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":[0.0007837752,0.001038085,0.0008347068,0.0003549442,0.0003861354,0.000916525,0.0004573336,0.0005446261,0.0009238322],"category_scores_gemma":[0.001678607,0.0004325781,0.0005184446,0.0007013511,0.000886564,0.0007853591,0.0009290228,0.0009712305,0.000300914],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006840185,"about_ca_system_score_gemma":0.001245277,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003506555,"about_ca_topic_score_gemma":0.00303529,"domain_scores_codex":[0.9992263,0.000272671,0.00003233548,0.0001034895,0.0002337964,0.0001314265],"domain_scores_gemma":[0.9993247,0.0003496759,0.0001195604,0.00005913843,0.0001091752,0.00003785376],"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":[0.00009425083,0.00003648666,0.0004303583,0.00005883718,0.00003580952,0.0001313502,0.00007815777,0.9560425,0.004211359,0.01472526,0.000838852,0.02331684],"study_design_scores_gemma":[0.000006307858,0.00002639872,0.00006516379,0.000003724306,0.000006011778,0.00001943641,0.0000119922,0.9962064,0.0007001957,0.002742134,0.000207473,0.000004678857],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03306191,0.0005357268,0.9627294,0.0002304073,0.0000363914,0.00002530371,0.00005087121,0.0001435779,0.003186383],"genre_scores_gemma":[0.9143264,0.0008217572,0.08143403,0.00009180816,0.00005365802,0.00009119976,0.00009926791,0.00004022239,0.003041785],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003506555,"threshold_uncertainty_score":0.006972253,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009149322917241175,"score_gpt":0.2129395996868872,"score_spread":0.203790276769646,"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."}}