{"id":"W2107207557","doi":"10.1109/icc.1997.609911","title":"Adaptive digital beamforming in cellular CDMA systems using noniterative signal subspace tracking","year":2002,"lang":"en","type":"article","venue":"","topic":"Wireless Communication Networks Research","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Beamforming; Computer science; WSDMA; Adaptive beamformer; Code division multiple access; Subspace topology; Algorithm; SIGNAL (programming language); Electronic engineering; Precoding; Artificial intelligence; Engineering; Telecommunications; MIMO","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":[0.0003186137,0.0003224912,0.0002034914,0.0001767836,0.0001982791,0.0003290159,0.0003496295,0.0003061786,0.001012729],"category_scores_gemma":[0.0008878807,0.0001267732,0.00014779,0.0002793451,0.0003217033,0.0004978888,0.0002985539,0.0003660512,0.0004292893],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002852369,"about_ca_system_score_gemma":0.0003772912,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001022144,"about_ca_topic_score_gemma":0.002033498,"domain_scores_codex":[0.9998158,0.00004870315,0.000008004663,0.00002134345,0.00009029643,0.00001593492],"domain_scores_gemma":[0.9997675,0.0001144221,0.00002883878,0.00002718643,0.00005249025,0.000009633093],"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":[0.0001792826,0.00008359683,0.001419828,0.0001145729,0.00003774057,0.0001151531,0.000134411,0.3410372,0.1196079,0.04340919,0.001002685,0.4928585],"study_design_scores_gemma":[0.00002173827,0.0001182662,0.000244521,0.000008691756,0.000009251665,0.00008210004,0.000008083063,0.9646932,0.02847071,0.003496845,0.002832715,0.00001368069],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.008484727,0.00007887781,0.9903881,0.00003442855,0.000009564056,0.00001344297,0.000005753819,0.0001867931,0.0007982355],"genre_scores_gemma":[0.2548744,0.0003333839,0.7413408,0.00007215369,0.00003556089,0.00007934968,0.00005442396,0.00004172384,0.003168213],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001022144,"threshold_uncertainty_score":0.003387988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09260808553566867,"score_gpt":0.2739568654626966,"score_spread":0.1813487799270279,"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."}}