{"id":"W4239722879","doi":"10.32920/ryerson.14648127.v1","title":"Resource Management in Cloud Radio Access Networks","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Radio access network; C-RAN; Resource allocation; Cloud computing; Radio resource management; Distributed computing; Computer network; Max-min fairness; Resource management (computing); Optimization problem; Base station; Wireless network; Wireless; Algorithm; 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":[0.001326643,0.0005281395,0.0007590048,0.0004020519,0.0009517596,0.002390319,0.001408053,0.0006511174,0.001420166],"category_scores_gemma":[0.002693217,0.0002485806,0.0004022123,0.0008228531,0.0007696868,0.001839888,0.001258214,0.0008433734,0.000290393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001841112,"about_ca_system_score_gemma":0.001779399,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006027617,"about_ca_topic_score_gemma":0.003699275,"domain_scores_codex":[0.998854,0.0003495776,0.00005481865,0.0001830578,0.0003199632,0.0002385573],"domain_scores_gemma":[0.9991661,0.0003943138,0.0000904003,0.00009434992,0.0001955748,0.00005923894],"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":[0.0001117329,0.00008206718,0.0007913748,0.0001442053,0.00003766429,0.0001988305,0.0001263413,0.7419431,0.005485058,0.1428733,0.003712157,0.1044942],"study_design_scores_gemma":[0.000006880121,0.00001762047,0.0001066805,0.00001052608,0.000005479408,0.00002868957,0.00004101071,0.9820114,0.0009676217,0.01419763,0.002599393,0.000006949984],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03791029,0.003099018,0.9417466,0.0007842081,0.000220354,0.0001951385,0.00006646696,0.0002998252,0.01567808],"genre_scores_gemma":[0.8721575,0.002140878,0.1202964,0.0002453951,0.0001520082,0.0001830298,0.00007555023,0.00006121804,0.004688042],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006027617,"threshold_uncertainty_score":0.01335829,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01347149719560119,"score_gpt":0.2461967031236809,"score_spread":0.2327252059280797,"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."}}