{"id":"W2042830833","doi":"10.1109/isssta.2006.311766","title":"Analysis of Throughput and Fairness of WCDMA Networks with Downlink Scheduling","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Maximum throughput scheduling; Proportionally fair; Computer science; Fairness measure; Scheduling (production processes); Telecommunications link; Throughput; Computer network; W-CDMA; Round-robin scheduling; Max-min fairness; Distributed computing; Code division multiple access; Mathematical optimization; Dynamic priority scheduling; Quality of service; Wireless; Mathematics; Resource allocation; 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":[0.003849674,0.0008392956,0.0009626636,0.001220259,0.001052014,0.002043201,0.001280268,0.0008877817,0.001278779],"category_scores_gemma":[0.01664616,0.0003929658,0.0004759425,0.001263723,0.001680253,0.002574775,0.0009342782,0.00105898,0.0002304144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003678764,"about_ca_system_score_gemma":0.002108348,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006191074,"about_ca_topic_score_gemma":0.002278633,"domain_scores_codex":[0.9966146,0.001207033,0.00008506174,0.0002460503,0.001226199,0.0006210239],"domain_scores_gemma":[0.9940785,0.004080624,0.0005447061,0.0004323298,0.0007653566,0.00009836388],"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":[0.0001314794,0.00004696047,0.0009057312,0.00006976254,0.00005033277,0.0001246257,0.0001146412,0.8263015,0.00475292,0.1498126,0.000490287,0.01719916],"study_design_scores_gemma":[0.000004217846,0.00001625319,0.0001727666,0.000007682342,0.000009738945,0.00002335724,0.00001704048,0.9840482,0.00157814,0.01371219,0.0004035915,0.000006845405],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1030908,0.001600666,0.8829629,0.0004551422,0.00008056706,0.00007273936,0.0001066578,0.0003280251,0.01130248],"genre_scores_gemma":[0.9639758,0.0007801522,0.0327007,0.00007822184,0.0001460485,0.0000968005,0.00005813131,0.00006212841,0.002101986],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006191074,"threshold_uncertainty_score":0.02669144,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002494869498609002,"score_gpt":0.1741920754447142,"score_spread":0.1716972059461052,"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."}}