{"id":"W4386753104","doi":"10.1016/j.phycom.2023.102179","title":"Secure precoding design for high-mobility systems with OTFS modulation","year":2023,"lang":"en","type":"article","venue":"Physical Communication","topic":"PAPR reduction in OFDM","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"Guangzhou Municipal Science and Technology Project; National Natural Science Foundation of China","keywords":"Precoding; Computer science; Telecommunications link; Eavesdropping; Maximization; Zero-forcing precoding; Artificial noise; Control theory (sociology); Algorithm; Mathematical optimization; Computer network; Mathematics; MIMO; Telecommunications; Wireless; Channel (broadcasting); Physical layer; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002252371,0.00009598544,0.0001268159,0.00004737007,0.0001233157,0.00003928298,0.0001894107,0.00004117267,0.000001425654],"category_scores_gemma":[0.0000289671,0.00009157901,0.00002762933,0.000285139,0.0000308526,0.000204267,0.00002724678,0.0001218999,0.00003487331],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009990669,"about_ca_system_score_gemma":0.000008263812,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001740885,"about_ca_topic_score_gemma":0.000002123348,"domain_scores_codex":[0.9994094,0.00008402764,0.000134414,0.0001193081,0.0001151377,0.0001377543],"domain_scores_gemma":[0.9989796,0.0003255594,0.00003971635,0.0005495249,0.00007343176,0.0000321587],"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":[0.00001862969,0.00003684738,0.00003932462,0.0001177857,0.00003334899,4.201196e-8,0.0005345273,0.9805688,0.007869561,0.007759753,0.001134865,0.001886512],"study_design_scores_gemma":[0.0002111932,0.00003706308,0.00262374,0.00004392118,0.00001565979,6.476273e-7,0.0000914665,0.9872563,0.003508439,0.005605964,0.000479909,0.0001256378],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7739972,0.00008559253,0.2222265,0.0002348455,0.0002249598,0.001133561,0.00001762965,0.001475262,0.0006045119],"genre_scores_gemma":[0.9962668,0.00002283493,0.0028769,0.000002278479,0.0001097133,0.0005317586,0.0001150016,0.0000314607,0.00004326147],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2222696,"threshold_uncertainty_score":0.3734484,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04605803015916991,"score_gpt":0.2730773790318172,"score_spread":0.2270193488726473,"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."}}