{"id":"W2946618393","doi":"10.1109/twc.2019.2916363","title":"Privacy Preservation via Beamforming for NOMA","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Engineering and Physical Sciences Research Council; National Natural Science Foundation of China","keywords":"Computer science; Beamforming; Noma; Single antenna interference cancellation; Quality of service; Transmission (telecommunications); Computer network; Artificial noise; Mathematical optimization; Telecommunications; Telecommunications link; Mathematics; Transmitter; 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":[0.001842583,0.001198044,0.0009796069,0.0006500321,0.0009726008,0.001449448,0.0006985852,0.001031399,0.002128963],"category_scores_gemma":[0.004252846,0.0004106234,0.0007896774,0.001522296,0.001360808,0.001874098,0.002086622,0.001339922,0.0008761319],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000728438,"about_ca_system_score_gemma":0.001326336,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009679501,"about_ca_topic_score_gemma":0.001432728,"domain_scores_codex":[0.9973254,0.001413269,0.0001136789,0.0002937744,0.0005434361,0.0003103533],"domain_scores_gemma":[0.9981065,0.00107539,0.0002004898,0.0003201466,0.0002330123,0.00006451859],"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":[0.0004400198,0.0001141013,0.001171415,0.0002496442,0.0001429969,0.0004734136,0.000306427,0.4772626,0.0401049,0.2575336,0.005830097,0.2163707],"study_design_scores_gemma":[0.00003501015,0.0001164578,0.0003056899,0.00002687839,0.00003013422,0.0002648042,0.00007186474,0.9190161,0.01001134,0.06592579,0.004148327,0.00004760123],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00483688,0.0003426464,0.9916848,0.0002379111,0.00003487204,0.00002343716,0.00005540123,0.0001400819,0.002643946],"genre_scores_gemma":[0.6369916,0.001736473,0.3549689,0.000508813,0.0001886472,0.0002321323,0.0002136408,0.00008367172,0.005076114],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002128963,"threshold_uncertainty_score":0.009744644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02746097866124859,"score_gpt":0.2661426336798034,"score_spread":0.2386816550185548,"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."}}