{"id":"W4388040437","doi":"10.1109/pimrc56721.2023.10294041","title":"Resource Allocation and Performance Analysis of Hybrid RSMA-NOMA in the Downlink","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Noma; Computer science; Telecommunications link; Single antenna interference cancellation; Resource allocation; Mathematical optimization; Max-min fairness; Interference (communication); Power (physics); Throughput; Maximization; Computer network; Distributed computing; Wireless; Mathematics; Telecommunications; Channel (broadcasting)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001777439,0.0008744719,0.0006772343,0.000574755,0.0005067555,0.001007623,0.000590803,0.0006046045,0.001511379],"category_scores_gemma":[0.003768101,0.0002895206,0.0004273645,0.0007229359,0.0008250237,0.0006830999,0.0006860191,0.0005221469,0.0002048463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001146821,"about_ca_system_score_gemma":0.0009217827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006964528,"about_ca_topic_score_gemma":0.004939893,"domain_scores_codex":[0.999099,0.0004610451,0.00002002538,0.00006606877,0.000177401,0.0001765061],"domain_scores_gemma":[0.9974401,0.001799162,0.0002406063,0.00008950822,0.0003525924,0.00007804589],"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":[0.00009103159,0.00002530299,0.000707666,0.00003795746,0.00002537699,0.00007372547,0.00002655603,0.9883565,0.001453366,0.005044654,0.0002626323,0.0038952],"study_design_scores_gemma":[0.000004014861,0.00003480348,0.0001758381,0.000002311225,0.000005303843,0.00001513419,0.00001323506,0.9990398,0.0002222191,0.0004310111,0.00005316607,0.000003114999],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.546863,0.00236608,0.4208833,0.0005933879,0.00008099787,0.0001404941,0.0001907491,0.0002982077,0.0285839],"genre_scores_gemma":[0.9890771,0.0002432708,0.009639157,0.00003135491,0.0000168392,0.0000330897,0.00002723406,0.00001177388,0.0009201757],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006964528,"threshold_uncertainty_score":0.01384801,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01358198019213792,"score_gpt":0.2269028644283681,"score_spread":0.2133208842362302,"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."}}