{"id":"W2077539535","doi":"10.1109/vetecf.2010.5594591","title":"Performance Analysis of Proportional Fair Scheduling in OFDMA Wireless Systems","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Subcarrier; Orthogonal frequency-division multiplexing; Computer science; Orthogonal frequency-division multiple access; Proportionally fair; Scheduling (production processes); Frequency-division multiple access; Maximum throughput scheduling; Wireless; Computer network; Max-min fairness; Round-robin scheduling; Real-time computing; Resource allocation; Dynamic priority scheduling; Mathematical optimization; Quality of service; Telecommunications; Channel (broadcasting); Mathematics","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":[0.0001041987,0.00008717668,0.0002129788,0.0002951936,0.00001644878,0.000008101726,0.00008190365,0.00007214097,0.00006000201],"category_scores_gemma":[0.000005893622,0.00008456788,0.0000374061,0.001007536,0.0000221456,0.000182844,0.00001190803,0.0001519416,0.000002359953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002444471,"about_ca_system_score_gemma":0.00001126782,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001522411,"about_ca_topic_score_gemma":0.0001005478,"domain_scores_codex":[0.9992971,0.000005684008,0.0003096395,0.0001094152,0.0001380708,0.0001400941],"domain_scores_gemma":[0.9996948,0.00002086071,0.00005303895,0.0001398421,0.00006267046,0.00002873533],"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":[0.000002362869,0.00001108675,0.09855584,0.00005117224,0.00007169374,3.536665e-7,0.00003124663,0.8928503,0.006226777,0.0006839114,0.000002589061,0.00151262],"study_design_scores_gemma":[0.00009340156,0.000003571993,0.03160416,0.00002351453,0.00003900113,4.777055e-7,0.00003113947,0.9662682,0.001828874,0.000002378168,0.00001210575,0.00009316031],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9053983,0.00003975963,0.09339464,0.000004769561,0.0002032308,0.00009715374,0.00000279756,0.0001090987,0.0007502579],"genre_scores_gemma":[0.9929273,0.00007505956,0.006840841,0.000001845054,0.00004053977,0.00002915707,0.00002451021,0.00001596506,0.00004482839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08752896,"threshold_uncertainty_score":0.3448578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004745498959516713,"score_gpt":0.200431107442742,"score_spread":0.1956856084832253,"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."}}