{"id":"W2148489950","doi":"10.1109/vetecf.2004.1400489","title":"Super-orthogonal space-time trellis coded cooperative diversity systems","year":2005,"lang":"en","type":"article","venue":"","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Pairwise error probability; Space–time trellis code; Trellis (graph); Computer science; Code (set theory); Antenna diversity; Theoretical computer science; Algorithm; Diversity gain; Spectral efficiency; Wireless; Cooperative diversity; Block code; Monte Carlo method; Wireless network; Fading; Mathematics; Telecommunications; Error floor; Decoding methods; Channel (broadcasting); Statistics","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":[0.001027102,0.0003752819,0.0004697808,0.0003260545,0.0003331593,0.0005521165,0.0006489049,0.0006143364,0.0008182797],"category_scores_gemma":[0.002562999,0.0001269974,0.0003094902,0.0008678454,0.0007781987,0.0007797873,0.000599771,0.0005088763,0.0001682133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005102851,"about_ca_system_score_gemma":0.0006253148,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00117766,"about_ca_topic_score_gemma":0.001633359,"domain_scores_codex":[0.9993001,0.0002424202,0.00002062984,0.00004724921,0.0003144417,0.00007512213],"domain_scores_gemma":[0.9971397,0.001572302,0.0003685536,0.0002702963,0.00057008,0.00007906942],"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":[0.0001370801,0.00004549876,0.001300089,0.0000955775,0.00006156463,0.000411257,0.0001370799,0.8004894,0.01716046,0.1587409,0.0006743807,0.02074679],"study_design_scores_gemma":[0.00001080943,0.0000688313,0.0002396992,0.000006552928,0.000008417256,0.0002028255,0.00002021628,0.9770678,0.002840789,0.01883237,0.000688244,0.00001346899],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.247616,0.0007379398,0.7367069,0.0002347075,0.00005320107,0.00005717988,0.000119572,0.0001238531,0.01435066],"genre_scores_gemma":[0.9594389,0.0003899443,0.03813557,0.00006857407,0.0000245998,0.00004354462,0.00005657002,0.0000125991,0.001829773],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00117766,"threshold_uncertainty_score":0.00543195,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03244459074918129,"score_gpt":0.2466223294133676,"score_spread":0.2141777386641863,"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."}}