{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001290987,0.0008659451,0.0009594341,0.000574764,0.0002495114,0.0005472977,0.0005812166,0.001016643,0.0008735067],"category_scores_gemma":[0.008081608,0.0004687398,0.0003588171,0.0008343811,0.0007294529,0.001122807,0.0007619663,0.0005997985,0.0003014665],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003901947,"about_ca_system_score_gemma":0.001027286,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001900584,"about_ca_topic_score_gemma":0.001768536,"domain_scores_codex":[0.9990106,0.0004219393,0.00004627681,0.000117221,0.0002991684,0.0001047647],"domain_scores_gemma":[0.9965678,0.002417792,0.0003395454,0.0002090455,0.0003990972,0.00006674871],"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":[0.0001706379,0.00002965895,0.0009115315,0.0001071388,0.00005280085,0.00007492113,0.00007900083,0.8958101,0.01163229,0.009854625,0.0003863409,0.08089082],"study_design_scores_gemma":[0.00001723322,0.00006631228,0.000306351,0.00000923514,0.0000156519,0.0000588066,0.000008512062,0.991626,0.004327187,0.003256752,0.0002939775,0.00001393923],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01262953,0.0001774877,0.9866806,0.00005368429,0.0000109458,0.00001138844,0.00002001136,0.00008975169,0.0003266734],"genre_scores_gemma":[0.6648121,0.000653657,0.332391,0.00009557902,0.0001090661,0.0001420025,0.0001849363,0.00006063003,0.00155107],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001900584,"threshold_uncertainty_score":0.006827474,"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."}}