{"id":"W2171250293","doi":"10.1109/tcomm.2005.849638","title":"Iterative Tree Search Detection for MIMO Wireless Systems","year":2005,"lang":"en","type":"article","venue":"IEEE Transactions on Communications","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":173,"is_retracted":false,"has_abstract":true,"ca_institutions":"Communications Research Centre Canada","funders":"","keywords":"MIMO; Turbo; Computer science; Quadrature amplitude modulation; Turbo code; Algorithm; Computational complexity theory; Tree (set theory); Wireless; Detection theory; Bit error rate; QAM; Electronic engineering; Mathematics; Decoding methods; Channel (broadcasting); Telecommunications; Engineering; Detector","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":[0.000636083,0.0003749235,0.0005096646,0.0004216891,0.0002354643,0.0005858726,0.0004866435,0.0006238757,0.001096308],"category_scores_gemma":[0.003004423,0.0002008888,0.000224985,0.0006089557,0.0005558543,0.0007358522,0.0005545483,0.0005589962,0.0004596217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003801878,"about_ca_system_score_gemma":0.0005255297,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004976442,"about_ca_topic_score_gemma":0.0006285374,"domain_scores_codex":[0.999342,0.0002598233,0.00002687067,0.00005344176,0.0002666358,0.00005114107],"domain_scores_gemma":[0.9988488,0.0007352229,0.0001032317,0.0001179624,0.0001663574,0.00002839695],"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":[0.0003857812,0.0000525327,0.0006380992,0.0002446701,0.00006749373,0.0002086412,0.0002032048,0.5075017,0.04895859,0.1633841,0.002449844,0.2759054],"study_design_scores_gemma":[0.0000186574,0.0000793841,0.00009036488,0.00001001579,0.000007099375,0.00008326249,0.000006445145,0.969915,0.006781472,0.02146151,0.001532928,0.00001377231],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01275259,0.0004066509,0.9849526,0.0000899227,0.000022664,0.00001607637,0.00001802831,0.0001614358,0.001579997],"genre_scores_gemma":[0.538376,0.0007716395,0.4570471,0.0001624211,0.0000802584,0.0001030459,0.00008844992,0.00004672493,0.003324355],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001096308,"threshold_uncertainty_score":0.003667533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03672285389025646,"score_gpt":0.2979098798032245,"score_spread":0.2611870259129681,"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."}}