{"id":"W2473225105","doi":"10.1109/tvt.2016.2582515","title":"Robust Optimization of SC-FDE-Based Multihop DF Relay Systems With Imperfect CSI","year":2016,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Cooperative Communication and Network Coding","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; China Scholarship Council","keywords":"SC-FDE; Relay; Computer science; Channel state information; Bit error rate; Optimization problem; Equalization (audio); Transmitter power output; Robustness (evolution); Mathematical optimization; Channel (broadcasting); Power (physics); Algorithm; Wireless; Mathematics; Computer network; Telecommunications; Transmitter","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":[0.000986338,0.001041106,0.001100668,0.00032831,0.0002535075,0.001216173,0.0007053027,0.001257169,0.001218033],"category_scores_gemma":[0.002248249,0.000440199,0.0005488183,0.0005050145,0.0007761591,0.0009180571,0.0007378159,0.0007672653,0.0002215917],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008771915,"about_ca_system_score_gemma":0.0008155385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003020503,"about_ca_topic_score_gemma":0.001711618,"domain_scores_codex":[0.9995104,0.0001626698,0.00002015644,0.0001158676,0.0001268471,0.00006404598],"domain_scores_gemma":[0.9991054,0.000580181,0.0001416706,0.00004666022,0.0001052245,0.00002093679],"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":[0.00002927115,0.00001171297,0.0001063492,0.00004377987,0.00002294777,0.00004947175,0.00002057875,0.9884915,0.001371414,0.005138852,0.0001293361,0.004584717],"study_design_scores_gemma":[0.000005340516,0.00002070577,0.00005173084,0.000002975409,0.000005624809,0.000009248349,0.00000609374,0.9981335,0.000376748,0.001282341,0.0001015432,0.000004151482],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02716376,0.000479511,0.968501,0.0002146102,0.00002583453,0.00003071809,0.00007446759,0.0001017161,0.003408364],"genre_scores_gemma":[0.9450604,0.0004708445,0.05111682,0.00006170868,0.00002865956,0.00008867755,0.00008549738,0.0000348238,0.003052719],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003020503,"threshold_uncertainty_score":0.006364465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02106477092944231,"score_gpt":0.2245679733228134,"score_spread":0.2035032023933711,"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."}}