{"id":"W2143968970","doi":"10.1109/vtcfall.2013.6692082","title":"Adaptive Modulation for MIMO Systems with Decision-Feedback Equalizer","year":2013,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"MIMO; Rayleigh fading; Fading; Computer science; Control theory (sociology); Transmitter; Spectral efficiency; Adaptive equalizer; Multipath propagation; Interference (communication); Signal-to-noise ratio (imaging); Algorithm; Equalization (audio); Channel (broadcasting); Telecommunications","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":[0.0004408783,0.0004589122,0.0002899479,0.0003099355,0.0002487859,0.00045839,0.0003210253,0.0004420159,0.001226221],"category_scores_gemma":[0.001385045,0.0001662522,0.0002931408,0.0004272006,0.0003530478,0.0005772188,0.0002715046,0.0004220691,0.00021265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006693209,"about_ca_system_score_gemma":0.0003655449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001602439,"about_ca_topic_score_gemma":0.002319708,"domain_scores_codex":[0.9996693,0.0001159107,0.000009952159,0.00003232816,0.0001359982,0.00003642317],"domain_scores_gemma":[0.9997155,0.0001692396,0.00002961987,0.00001907693,0.00006222072,0.000004298236],"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":[0.0000579377,0.00003556529,0.0007736425,0.0001362222,0.0000565129,0.0001927012,0.00009640011,0.8650371,0.01130793,0.07443117,0.001052154,0.04682254],"study_design_scores_gemma":[0.000003903827,0.00003600714,0.0002362533,0.000009425201,0.000008308696,0.00004869902,0.000007685659,0.9926307,0.0008314076,0.005293015,0.0008896686,0.000005010917],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03201927,0.002860955,0.9568005,0.0002854213,0.0001163282,0.00003322988,0.00003499548,0.0001041792,0.007745107],"genre_scores_gemma":[0.9347782,0.002709416,0.05828192,0.0001271704,0.0002099801,0.00006543376,0.00003457953,0.00002238547,0.003770946],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001602439,"threshold_uncertainty_score":0.004856229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0113087535071064,"score_gpt":0.2093333098564308,"score_spread":0.1980245563493244,"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."}}