{"id":"W2136768212","doi":"10.1109/wcnc.2008.312","title":"Adaptive Tuning of MIMO-Enabled 802.11e WLANs with Network Utility Maximization","year":2008,"lang":"en","type":"article","venue":"","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Computer network; Physical layer; MIMO; Spatial multiplexing; Quality of service; Wireless network; Throughput; Wireless; Wi-Fi; Multi-user MIMO; Cross-layer optimization; Channel (broadcasting); Telecommunications","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":[0.001795307,0.000523906,0.0006523476,0.0003104755,0.0003231933,0.0007123211,0.0009511418,0.000495361,0.0006036581],"category_scores_gemma":[0.003527841,0.0003240485,0.000260314,0.0003313058,0.0006500711,0.0005739508,0.0008368822,0.0006283075,0.0001560987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007566769,"about_ca_system_score_gemma":0.0003662261,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001328395,"about_ca_topic_score_gemma":0.00138597,"domain_scores_codex":[0.9989616,0.000407702,0.00003170201,0.0001215061,0.0002876623,0.0001898786],"domain_scores_gemma":[0.9988711,0.0006895871,0.0001246284,0.0000755829,0.0001758463,0.00006311551],"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":[0.0001699566,0.0001306396,0.001596836,0.00004623722,0.0000468238,0.0001445387,0.00009596851,0.933926,0.02096362,0.007039343,0.0003718525,0.0354682],"study_design_scores_gemma":[0.00001419688,0.00003989405,0.0003534275,0.000002407071,0.000007325356,0.00003348023,0.00001168955,0.9955605,0.002762017,0.001001522,0.0002061238,0.000007475508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.131253,0.0004792217,0.8601984,0.0002095398,0.00004865968,0.00005842938,0.00001736902,0.0004138152,0.00732159],"genre_scores_gemma":[0.9877438,0.00007419492,0.01163621,0.00003349877,0.0000125763,0.00002099488,0.000006104723,0.00001084637,0.0004617371],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001795307,"threshold_uncertainty_score":0.009494603,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03014707433726018,"score_gpt":0.2227967732326558,"score_spread":0.1926496988953956,"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."}}