{"id":"W3009628117","doi":"10.1109/globecom38437.2019.9013439","title":"Joint Resource Allocation in NOMA Systems with Imperfect SIC","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Precoding; Computer science; Resource allocation; Base station; Beamforming; Single antenna interference cancellation; Cluster analysis; Mathematical optimization; Interference (communication); Joint (building); Optimization problem; Imperfect; Transmitter power output; Noma; Channel (broadcasting); Telecommunications link; Algorithm; Computer network; Telecommunications; Mathematics; MIMO; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006666675,0.00008035527,0.0001137605,0.0001063157,0.00001084989,0.00001421647,0.0001672646,0.00005342004,0.00001204675],"category_scores_gemma":[0.000009223212,0.00006673927,0.000009737851,0.0001987435,0.00001609207,0.0001049809,0.00003658482,0.0001336481,0.0001009456],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009150394,"about_ca_system_score_gemma":0.000004879694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002719423,"about_ca_topic_score_gemma":0.00003000614,"domain_scores_codex":[0.9995743,0.00001232144,0.0001340188,0.00009336574,0.00006736459,0.0001186477],"domain_scores_gemma":[0.9993798,0.00003615991,0.00002016922,0.000537461,0.00001424437,0.00001221062],"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":[0.000004534838,0.00001199855,0.003231752,0.00008122195,0.00001063886,9.458753e-7,0.0001137086,0.9637642,0.01604433,0.01135758,0.0001356134,0.00524348],"study_design_scores_gemma":[0.001222513,0.000209203,0.01533755,0.0003691257,0.000004819266,0.00002474035,0.004209401,0.9085349,0.05702931,0.0003209467,0.01203191,0.000705622],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9327471,0.0006580777,0.03282767,0.0001274009,0.00004543508,0.0003905538,5.835857e-7,0.001540121,0.03166312],"genre_scores_gemma":[0.9980152,0.0000509056,0.001571145,0.000008488337,0.000004181191,0.00004901447,0.000004167316,0.00002117898,0.00027578],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0652681,"threshold_uncertainty_score":0.2721549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008652655372022531,"score_gpt":0.1928284925256819,"score_spread":0.1841758371536594,"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."}}