{"id":"W2147893709","doi":"10.1109/glocom.2004.1378427","title":"Joint channel and frequency offset estimation and training sequence design for MIMO systems over frequency selective channels","year":2005,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Estimator; Fading; MIMO; Frequency offset; Channel (broadcasting); Computer science; Impulse response; Joint (building); Control theory (sociology); Offset (computer science); Algorithm; Mathematics; Statistics; Telecommunications; Orthogonal frequency-division multiplexing; Engineering; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002940088,0.0002125815,0.0002521582,0.0001427486,0.0001294138,0.00006465783,0.0001145276,0.0001198773,0.000004987065],"category_scores_gemma":[0.00009822462,0.0002168984,0.00002455107,0.0001388553,0.00005968416,0.0006442089,0.00002452789,0.0001489199,0.000001895421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001544726,"about_ca_system_score_gemma":0.0000220814,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005205377,"about_ca_topic_score_gemma":0.00001860345,"domain_scores_codex":[0.9990337,0.00004396791,0.0003240545,0.0002359916,0.0001005385,0.0002616886],"domain_scores_gemma":[0.9993358,0.000168776,0.00007481395,0.0002447025,0.00009271905,0.00008323348],"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":[0.00002549108,0.00007106896,0.00009136098,0.0008508948,0.0002060905,0.000003611882,0.01176437,0.5854779,0.1897161,0.09528305,0.001633044,0.1148771],"study_design_scores_gemma":[0.0002236838,0.00007474097,0.00007145043,0.0001431989,0.00001179567,0.00002681228,0.0001710314,0.9646485,0.02135432,0.01294644,0.000044334,0.0002837325],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01376214,0.001554284,0.9820268,0.0001250736,0.00006742882,0.0009636519,0.00002407178,0.0008366783,0.0006399162],"genre_scores_gemma":[0.7431363,0.0002857216,0.2560119,0.00003325096,0.00004581815,0.000410399,0.00001310687,0.00003653313,0.00002692399],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7293742,"threshold_uncertainty_score":0.8844861,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0635505157226816,"score_gpt":0.2826217029984988,"score_spread":0.2190711872758172,"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."}}