{"id":"W2098061185","doi":"10.1109/tsp.2008.2008542","title":"MIMO Minimum Total MSE Transceiver Design With Imperfect CSI at Both Ends","year":2008,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":177,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"MIMO; Mean squared error; Minimum mean square error; Channel state information; Channel (broadcasting); Transceiver; Control theory (sociology); Computer science; Joint (building); Mathematics; Telecommunications; Statistics; Engineering; Wireless","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008929072,0.0003575017,0.0002943748,0.0002093082,0.0004958625,0.00003839371,0.0001119107,0.0001448751,0.0001302522],"category_scores_gemma":[9.146393e-7,0.0003360049,0.00009565356,0.000447769,0.0001015358,0.0006368494,4.467004e-7,0.0003002842,0.00004169262],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002562458,"about_ca_system_score_gemma":0.00007685395,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005096767,"about_ca_topic_score_gemma":0.000009935758,"domain_scores_codex":[0.9985695,0.00004819828,0.000323608,0.0003616762,0.000277843,0.0004191592],"domain_scores_gemma":[0.9994629,0.00008036343,0.0000574507,0.0001808429,0.0000753335,0.0001430905],"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":[0.0001839526,0.00005823169,0.000005766007,0.0001097518,0.00004841039,0.00003820811,0.001286702,0.9303123,0.05819385,3.321404e-7,0.00005855575,0.009703881],"study_design_scores_gemma":[0.001886203,0.0004443287,0.00003454985,0.0003298077,0.0001238536,0.0008232,0.0001507568,0.6102933,0.3849621,0.000006885618,0.0001113704,0.0008336584],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03390545,0.000311019,0.9638655,0.00001110564,0.0001432396,0.0003435228,0.00001407911,0.0006270894,0.0007790582],"genre_scores_gemma":[0.9846436,0.00004423875,0.01415891,0.00002257096,0.00006883271,0.00009143028,0.000003805309,0.0001261608,0.0008404418],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9507381,"threshold_uncertainty_score":0.9999092,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01669496514568091,"score_gpt":0.2137949191906762,"score_spread":0.1970999540449953,"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."}}