{"id":"W2035625138","doi":"10.1109/glocom.2005.1577379","title":"Detector for Alamouti space-time coding in Rayleigh fading MIMO channels with randomly distributed timing drift","year":2005,"lang":"en","type":"article","venue":"GLOBECOM '05. IEEE Global Telecommunications Conference, 2005.","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Samsung","keywords":"Detector; Algorithm; Estimator; Rayleigh fading; Channel state information; Channel (broadcasting); Fading; MIMO; Coding (social sciences); Computer science; Mathematics; Block code; Space–time code; Statistics; Topology (electrical circuits); Telecommunications; Decoding methods; Wireless; Combinatorics","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":[0.006240351,0.001179523,0.00116644,0.001243218,0.0007156064,0.001361452,0.00106213,0.001570925,0.001408249],"category_scores_gemma":[0.02646047,0.0006108618,0.0006271295,0.001133507,0.001921874,0.001979475,0.001286707,0.001189181,0.0004849314],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002582752,"about_ca_system_score_gemma":0.002663369,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00321674,"about_ca_topic_score_gemma":0.002525306,"domain_scores_codex":[0.9978979,0.0006843022,0.00007933666,0.0002312979,0.0007832992,0.000323845],"domain_scores_gemma":[0.9805892,0.01503546,0.001903446,0.0006763354,0.001618576,0.000177072],"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":[0.0003206856,0.00003082301,0.001492018,0.000107128,0.00008413129,0.000165625,0.0001381231,0.9194651,0.00499272,0.05554099,0.0007239497,0.0169387],"study_design_scores_gemma":[0.0000152755,0.00004616348,0.0002199182,0.00001408414,0.00001424909,0.00009786079,0.00001191546,0.9923614,0.001729063,0.005322477,0.0001502051,0.00001742134],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0652635,0.0009901531,0.9299735,0.0002974777,0.00004535251,0.0000813306,0.0001602302,0.0004075919,0.002780849],"genre_scores_gemma":[0.8835939,0.0008514278,0.112519,0.0001716232,0.0000888271,0.0001765144,0.0002583334,0.00009146333,0.002248984],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006240351,"threshold_uncertainty_score":0.03300256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02187344640656313,"score_gpt":0.2658517260727545,"score_spread":0.2439782796661914,"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."}}