{"id":"W2920856460","doi":"10.1109/tsp.2019.2905833","title":"Multi-User Regularized Zero-Forcing Beamforming","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute for Computational Science and Technology; Queen's University; Queen's University Belfast; Royal Academy of Engineering; National Science Foundation","keywords":"Beamforming; Zero (linguistics); Computer science; Signal processing; Mathematics; Algorithm; Speech recognition; Telecommunications; Radar","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007210324,0.0007850051,0.0006488943,0.0002241987,0.000214561,0.0006167408,0.0005810667,0.0008166303,0.002093647],"category_scores_gemma":[0.001540237,0.0002584363,0.0005078045,0.000474424,0.0006082035,0.0006667544,0.0007247684,0.0007652486,0.0007275188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003442997,"about_ca_system_score_gemma":0.0005856203,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007175602,"about_ca_topic_score_gemma":0.0008603599,"domain_scores_codex":[0.9996037,0.0001527444,0.00001556237,0.00006723229,0.0001218292,0.00003894834],"domain_scores_gemma":[0.9995205,0.0002467475,0.00005609518,0.00006926064,0.00008791593,0.00001942617],"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":[0.0001699716,0.00003206602,0.0002914472,0.0001246076,0.00004200737,0.0001259046,0.00007098936,0.8817683,0.01558482,0.0508131,0.002415447,0.04856133],"study_design_scores_gemma":[0.000009714946,0.00002458513,0.0000505763,0.000006635457,0.000004188268,0.00003703379,0.000005841291,0.9913794,0.001665353,0.005996097,0.0008109111,0.000009689289],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004775719,0.00008604283,0.9925444,0.00008560183,0.00001991668,0.00002028954,0.0000476655,0.0001306372,0.002289694],"genre_scores_gemma":[0.4095474,0.0004878746,0.5829216,0.0002010861,0.0000638882,0.0001874653,0.0002576834,0.00007202047,0.00626094],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002093647,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01204631266851376,"score_gpt":0.2289075523073256,"score_spread":0.2168612396388118,"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."}}