{"id":"W2155750052","doi":"10.1109/vetecs.2008.544","title":"Scheduling for MIMO Broadcast Channels with Linear Receivers and Partial Channel State Information","year":2008,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"MIMO; Channel state information; Computer science; Telecommunications link; Scheduling (production processes); Base station; Multiplexing; Precoding; Channel (broadcasting); Computer network; Multi-user MIMO; Spatial multiplexing; Real-time computing; Telecommunications; Wireless; Mathematics; Mathematical optimization","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":[0.0007134818,0.0003718502,0.0004996403,0.0002333158,0.0004662277,0.0004458644,0.000373948,0.0002854352,0.001408895],"category_scores_gemma":[0.001913197,0.0002015346,0.0002346597,0.0004327851,0.0004508955,0.000356299,0.0003548942,0.0002904803,0.0002353601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005929277,"about_ca_system_score_gemma":0.000987631,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001515893,"about_ca_topic_score_gemma":0.003479724,"domain_scores_codex":[0.9995319,0.0001964816,0.00001404656,0.00004571722,0.00013165,0.00008017595],"domain_scores_gemma":[0.9990286,0.0006001263,0.0001339592,0.00008139521,0.0001158673,0.00004010929],"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":[0.0004267096,0.00007047884,0.0007995909,0.0002411442,0.00003866805,0.0001482841,0.0001548332,0.8385478,0.03059718,0.03541071,0.001974231,0.09159028],"study_design_scores_gemma":[0.00002697003,0.0001177001,0.0003081462,0.000006243011,0.00001133295,0.00004836827,0.00002645239,0.9888447,0.004154309,0.005684121,0.0007604682,0.00001107529],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04871054,0.0004763037,0.9478146,0.0001265247,0.00004032428,0.00004594973,0.00006770263,0.0001093261,0.002608699],"genre_scores_gemma":[0.8932947,0.0005577508,0.1040634,0.00005174836,0.00007531691,0.000072013,0.00009027932,0.00002180794,0.001772994],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001515893,"threshold_uncertainty_score":0.004713237,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01287659188087483,"score_gpt":0.2055764972637127,"score_spread":0.1926999053828378,"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."}}