{"id":"W4205434634","doi":"10.1109/lwc.2021.3139024","title":"MSE-Based Joint Transceiver and Passive Beamforming Designs for Intelligent Reflecting Surface-Aided MIMO Systems","year":2021,"lang":"en","type":"article","venue":"IEEE Wireless Communications Letters","topic":"Advanced Wireless Communication Technologies","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Kingston Health Sciences Centre; Queen's University","funders":"Institute for Information and Communications Technology Promotion; National Research Foundation","keywords":"Beamforming; MIMO; Mean squared error; Transceiver; Computer science; Minification; Minimum mean square error; Algorithm; Filter (signal processing); Control theory (sociology); Mathematical optimization; Mathematics; Telecommunications; Wireless; Artificial intelligence; Statistics; Computer vision","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":[0.00086341,0.001350844,0.0007096136,0.0003115373,0.0002363687,0.0007490398,0.0009246159,0.0007879445,0.001954668],"category_scores_gemma":[0.002206984,0.0005055616,0.0005095777,0.0004770374,0.0005054301,0.001432861,0.0009542147,0.000871447,0.0009655756],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003175173,"about_ca_system_score_gemma":0.0006140685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004312133,"about_ca_topic_score_gemma":0.0009515673,"domain_scores_codex":[0.9992201,0.0002206375,0.00004118494,0.0001024721,0.0003460578,0.00006954782],"domain_scores_gemma":[0.999221,0.0002722845,0.0001170021,0.000091687,0.0002673595,0.0000307079],"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":[0.000197481,0.00009269681,0.0007923996,0.0002399417,0.0001302926,0.0001505901,0.0002139027,0.6410874,0.08491561,0.03918003,0.002319672,0.23068],"study_design_scores_gemma":[0.00001683947,0.0001855717,0.0001563663,0.00001269433,0.000019955,0.0001193721,0.00002050802,0.9808925,0.01283379,0.003513121,0.002209092,0.00002032143],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002782503,0.00008502619,0.9959748,0.00003980349,0.00001356588,0.00001149724,0.00001049148,0.00007750521,0.001004777],"genre_scores_gemma":[0.3930327,0.0005241892,0.6002892,0.0001986611,0.0001065235,0.0001703999,0.0001592026,0.00007427172,0.005444795],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001954668,"threshold_uncertainty_score":0.006539047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09376458531483889,"score_gpt":0.2993393769447553,"score_spread":0.2055747916299164,"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."}}