{"id":"W2138796389","doi":"10.1109/iswpc.2009.4800596","title":"Multi-Dimensional Beamforming for Adaptive MIMO Systems","year":2009,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Beamforming; MIMO; Computer science; Adaptive beamformer; Algorithm; Bandwidth (computing); Bit error rate; Dimension (graph theory); Precoding; WSDMA; Electronic engineering; Telecommunications; Mathematics; Decoding methods; Engineering","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":[0.0004446796,0.000735514,0.0004087318,0.0003237802,0.000398364,0.0005199664,0.0004008225,0.0006333692,0.00222449],"category_scores_gemma":[0.001149464,0.0002387264,0.0002995315,0.0006997375,0.0004706658,0.0007383621,0.0006934032,0.0007488175,0.0009754792],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003671161,"about_ca_system_score_gemma":0.0003535023,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003316759,"about_ca_topic_score_gemma":0.0006232766,"domain_scores_codex":[0.9996045,0.0001573182,0.00003062004,0.00004815476,0.0001302565,0.00002913862],"domain_scores_gemma":[0.9995016,0.0001760951,0.00005659027,0.0000921738,0.0001459895,0.00002753716],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000249914,0.00004856687,0.0007322861,0.0003722967,0.00008618103,0.0002194851,0.0001834848,0.2460756,0.1269455,0.2238791,0.007482511,0.3937251],"study_design_scores_gemma":[0.00002920991,0.0002125396,0.0003322331,0.00006770621,0.0000289967,0.0003872562,0.00003487737,0.9078636,0.01781392,0.05461884,0.01852538,0.00008542612],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002620018,0.0009202732,0.9936679,0.0001909663,0.0001040655,0.00001691093,0.00002349563,0.0001385361,0.002317944],"genre_scores_gemma":[0.3604119,0.003714502,0.629378,0.0005368709,0.0004215188,0.0002866921,0.0001586015,0.00005715819,0.005034782],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00222449,"threshold_uncertainty_score":0.00744164,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02798756160270141,"score_gpt":0.2706798735846456,"score_spread":0.2426923119819442,"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."}}