{"id":"W2129320079","doi":"10.1109/glocom.2009.5425344","title":"Power Allocation for Cooperative Diversity Networks with Inaccurate CSI: A Robust and Constrained Kalman Filter Approach","year":2009,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Kalman filter; Robustness (evolution); Computer science; Channel state information; Channel (broadcasting); Control theory (sociology); Mathematical optimization; Fading; Wireless; Mathematics; Telecommunications; Artificial intelligence","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":[0.0009037924,0.0006418964,0.0008310173,0.0003230463,0.0004319829,0.0007819489,0.0008971068,0.0007585147,0.0008786199],"category_scores_gemma":[0.002474833,0.0003943859,0.0004484308,0.0003720365,0.0006942892,0.001498175,0.0007565529,0.0008008815,0.0002666296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000816791,"about_ca_system_score_gemma":0.0008927168,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004799943,"about_ca_topic_score_gemma":0.003308746,"domain_scores_codex":[0.9994885,0.0001395618,0.00002764099,0.0001149371,0.000173657,0.00005578301],"domain_scores_gemma":[0.9992639,0.0004203304,0.00009815356,0.00007837733,0.0001235499,0.00001565774],"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":[0.00003994398,0.00002137807,0.0001952764,0.00005494975,0.00003254296,0.00005034947,0.00009997806,0.9145119,0.003409463,0.02240537,0.0005540584,0.05862485],"study_design_scores_gemma":[0.000004641139,0.00001502304,0.00004017806,0.000003646458,0.000005502371,0.00001229287,0.00000549482,0.9957891,0.0006946098,0.003054625,0.0003684523,0.000006297404],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002046569,0.0001177307,0.9973102,0.00003977541,0.000009377723,0.000005998475,0.000004934573,0.00005935252,0.0004060088],"genre_scores_gemma":[0.764182,0.0007213309,0.2316779,0.0001207816,0.0001141828,0.0001474753,0.00005223607,0.00008143148,0.002902739],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004799943,"threshold_uncertainty_score":0.009544015,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04223310646049603,"score_gpt":0.2491552241672676,"score_spread":0.2069221177067716,"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."}}