{"id":"W3172818029","doi":"10.1109/tcomm.2021.3088898","title":"Secrecy-Energy Efficient Hybrid Beamforming for Satellite-Terrestrial Integrated Networks","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Satellite Communication Systems","field":"Engineering","cited_by":406,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; McGill University","funders":"Shanghai Aerospace Science and Technology Innovation Foundation; Nanjing University of Posts and Telecommunications; National Natural Science Foundation of China","keywords":"Beamforming; Telecommunications link; Computer science; Mathematical optimization; Optimization problem; Convex optimization; Iterative method; Base station; Communications satellite; Satellite; Algorithm; Mathematics; Telecommunications; Regular polygon; Engineering","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":[0.0007219174,0.0008082145,0.0005094954,0.000278779,0.0002478522,0.0005597846,0.00043206,0.0005291178,0.001249955],"category_scores_gemma":[0.001002722,0.0002636301,0.0003530503,0.0007817723,0.0005730414,0.0008672197,0.000703569,0.0005406757,0.0002994798],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000423539,"about_ca_system_score_gemma":0.0004379408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009061038,"about_ca_topic_score_gemma":0.001200816,"domain_scores_codex":[0.9995868,0.0001550115,0.00001513384,0.00005287382,0.0001368462,0.00005345556],"domain_scores_gemma":[0.999554,0.0002391463,0.00007827308,0.00004055254,0.00007116134,0.00001683571],"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":[0.00007974898,0.00002704025,0.0003520667,0.00007036105,0.00003994633,0.00007021612,0.00004685264,0.91496,0.01289267,0.03185804,0.0004889235,0.03911412],"study_design_scores_gemma":[0.000007119876,0.00005087,0.00006542405,0.000005399286,0.000007896355,0.00002840551,0.00001085084,0.993538,0.002087495,0.00369315,0.0004990279,0.00000649607],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008980053,0.0002117264,0.9890276,0.00005006429,0.00001097098,0.00001222287,0.00001762559,0.00004265234,0.001647067],"genre_scores_gemma":[0.7903982,0.0008837674,0.205254,0.000102603,0.00004704655,0.00009235245,0.00007730979,0.00002614308,0.003118556],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001249955,"threshold_uncertainty_score":0.004181564,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03608583246600989,"score_gpt":0.257239790081947,"score_spread":0.2211539576159371,"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."}}