{"id":"W2132334733","doi":"10.1109/glocom.2006.618","title":"WLC01-4: MIMO Precoder Design Based on Spatial and Path Correlation Information for Frequency-Selective Channels","year":2006,"lang":"en","type":"article","venue":"Globecom","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"MIMO; Spatial correlation; Fading; Precoding; Channel (broadcasting); Path (computing); Uncorrelated; Channel capacity; Algorithm; Computer science; Correlation; Mathematics; Path loss; Topology (electrical circuits); Control theory (sociology); Electronic engineering; Telecommunications; Statistics; Engineering; Wireless; Computer network; Artificial intelligence; Geometry","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001066898,0.0001393113,0.0001216707,0.0001005192,0.00007330764,0.00004287288,0.00003965164,0.0001024237,0.00001009148],"category_scores_gemma":[0.00004540114,0.0001494834,0.00002472218,0.0001051934,0.000009568355,0.0004831851,0.000003946062,0.00006355687,0.0000153997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001473459,"about_ca_system_score_gemma":0.00001841151,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001026388,"about_ca_topic_score_gemma":0.00003421182,"domain_scores_codex":[0.9993758,0.00002301182,0.0002370823,0.0001126513,0.000081877,0.0001696035],"domain_scores_gemma":[0.9996142,0.00009506606,0.00007181058,0.0001019587,0.00008720513,0.00002973516],"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":[0.00002458248,0.00000909996,0.0003139549,0.00004035654,0.000005298168,1.443667e-7,0.0000897456,0.9943625,0.0001217775,0.0002416402,0.001328228,0.003462633],"study_design_scores_gemma":[0.0007065635,0.00009653791,0.0009485243,0.00003700908,0.00001045542,0.000001260026,0.00001163892,0.99478,0.001454207,0.00138042,0.0004089235,0.0001644676],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00103571,0.00004227896,0.9953486,0.00001937574,0.0004589566,0.0008899084,0.00004193816,0.0002259255,0.001937328],"genre_scores_gemma":[0.9456861,0.000003120594,0.05369418,0.00003393025,0.0001250594,0.000163852,0.0002377258,0.00002319598,0.00003282732],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9446504,"threshold_uncertainty_score":0.6095756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006626735969828236,"score_gpt":0.1920704337935756,"score_spread":0.1854436978237474,"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."}}