{"id":"W2101624054","doi":"10.1109/twc.2007.05317","title":"An iterative groupwise multiuser detector for overloaded MIMO applications","year":2007,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Canada Research Chairs","keywords":"Multiuser detection; Computer science; MIMO; Detector; Iterative method; Wireless; Computer network; Algorithm; Mathematical optimization; Telecommunications; Mathematics; Beamforming","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0006400016,0.0004378924,0.0004972357,0.0003092425,0.0002923127,0.0005377019,0.0005765914,0.000748805,0.0007124837],"category_scores_gemma":[0.001738129,0.0002133983,0.0002767433,0.0003627984,0.0004103853,0.0006865394,0.0007074171,0.0006400863,0.0004175181],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002546432,"about_ca_system_score_gemma":0.0005850003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003266278,"about_ca_topic_score_gemma":0.0006925173,"domain_scores_codex":[0.9995849,0.0001378355,0.00002006624,0.00005319052,0.0001614706,0.00004259037],"domain_scores_gemma":[0.9994193,0.0002603025,0.00005686053,0.00008923442,0.0001411513,0.00003317943],"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":[0.0005034438,0.0001798931,0.001991175,0.0001210914,0.0001076228,0.0004045343,0.0002980675,0.3762391,0.1391405,0.07032382,0.003409642,0.407281],"study_design_scores_gemma":[0.00001275254,0.0001309673,0.0001753787,0.000004887789,0.000009982638,0.000176947,0.000009302785,0.9699367,0.02086775,0.006771112,0.001887541,0.00001658021],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01225055,0.00009923909,0.9865857,0.00008820498,0.00002358039,0.00001727106,0.00001313315,0.0001913239,0.0007310153],"genre_scores_gemma":[0.3590679,0.0001692936,0.6381392,0.0001270062,0.0000586271,0.00005637307,0.00004404127,0.00002636512,0.0023112],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.000748805,"threshold_uncertainty_score":0.003384709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02379326473246458,"score_gpt":0.3010223177188317,"score_spread":0.2772290529863671,"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."}}