{"id":"W3214130165","doi":"10.1109/tvt.2021.3124928","title":"Robust Beamforming for Enhancing User Fairness in Multibeam Satellite Systems With NOMA","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Satellite Communication Systems","field":"Engineering","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Telecommunications link; Mathematical optimization; Computer science; Beamforming; Channel (broadcasting); Optimization problem; Convex optimization; Transmission (telecommunications); Spectral efficiency; Quality of service; Algorithm; Mathematics; Regular polygon; Computer network; Telecommunications","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":[0.001600679,0.001052776,0.001004583,0.0004929246,0.0008386948,0.000854668,0.001019546,0.0007364355,0.001322948],"category_scores_gemma":[0.002989261,0.0003278046,0.0004463916,0.0008177984,0.0009272847,0.001306344,0.001317697,0.0008773901,0.0003436222],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005681433,"about_ca_system_score_gemma":0.0008854466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001461667,"about_ca_topic_score_gemma":0.002295486,"domain_scores_codex":[0.9984321,0.0006520293,0.0000616515,0.0002064134,0.0004080865,0.0002396478],"domain_scores_gemma":[0.9986119,0.0008213604,0.0001629957,0.0001672082,0.0001698809,0.00006665816],"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":[0.0005171192,0.0001544464,0.001472903,0.0001481134,0.0001013951,0.0003300893,0.0002398193,0.7631556,0.043717,0.06695168,0.001614467,0.1215973],"study_design_scores_gemma":[0.00001463117,0.00007745021,0.0001353854,0.000005300803,0.00001287525,0.00007208985,0.00002162822,0.9894838,0.003431122,0.006067927,0.0006618928,0.00001589184],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01322065,0.0002405063,0.9845769,0.00007957377,0.00004009059,0.00002184807,0.00001601249,0.0001489961,0.001655461],"genre_scores_gemma":[0.8688498,0.0002854135,0.1289356,0.0001851304,0.0001076166,0.00006728768,0.00003072044,0.00004999271,0.001488461],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001600679,"threshold_uncertainty_score":0.00846535,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01902309110633439,"score_gpt":0.2171596426561495,"score_spread":0.1981365515498151,"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."}}