{"id":"W2972189300","doi":"10.1109/tcomm.2019.2939473","title":"Joint Transmission Scheduling and Power Allocation in Non-Orthogonal Multiple Access","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Engineering and Physical Sciences Research Council; National Natural Science Foundation of China","keywords":"Computer science; Scheduling (production processes); Telecommunications link; Efficient energy use; Base station; Single antenna interference cancellation; Throughput; Noma; Optimization problem; Heuristic; Multiplexing; Interference (communication); Mathematical optimization; Channel (broadcasting); Computer network; Wireless; Engineering; Algorithm; Telecommunications; Electrical 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":[0.0001385029,0.0001802138,0.0001980557,0.0003752169,0.0001827169,0.00004947392,0.0008203681,0.0001468616,0.00005110365],"category_scores_gemma":[0.000007468322,0.0002021969,0.00005510577,0.0004219081,0.0001097792,0.0005080689,0.00001557723,0.0006809828,0.0000483687],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000109255,"about_ca_system_score_gemma":0.00002105099,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002168001,"about_ca_topic_score_gemma":0.0001182457,"domain_scores_codex":[0.9990624,0.00005194498,0.0003655914,0.0001971444,0.0001248924,0.0001979894],"domain_scores_gemma":[0.9979376,0.000260799,0.00004785284,0.001645627,0.00005296056,0.000055175],"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":[0.00001637703,0.000226305,0.0004333114,0.00005580725,0.00003506379,3.907116e-7,0.0004890205,0.8670968,0.04794704,0.0007515646,0.00001055696,0.08293773],"study_design_scores_gemma":[0.001064339,0.00005271228,0.007729457,0.0002782074,0.00001250622,0.000006433238,0.0005126843,0.9239731,0.06349879,0.001223067,0.001201983,0.0004466968],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2104177,0.0004508967,0.7860504,0.0008551467,0.00009938866,0.0004626406,0.00001229614,0.000511518,0.001140023],"genre_scores_gemma":[0.9759942,0.003433799,0.02022493,0.00004156874,0.000002161782,0.0002099488,0.00001327727,0.00004041656,0.0000396521],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7658255,"threshold_uncertainty_score":0.8245351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02738883674165251,"score_gpt":0.2731394315955342,"score_spread":0.2457505948538817,"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."}}