{"id":"W2020901307","doi":"10.1109/vtcfall.2014.6965953","title":"Efficient and Accurate Semiblind Estimation of MIMO-OFDM Doubly-Selective Channels","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Orthogonal frequency-division multiplexing; Fading; Kalman filter; Computer science; MIMO; Channel (broadcasting); MIMO-OFDM; Block (permutation group theory); Algorithm; Spectral efficiency; Control theory (sociology); Electronic engineering; Mathematics; Telecommunications; 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":[0.0005546012,0.0004921856,0.0006965429,0.0003703806,0.0003384702,0.0005979369,0.0006300233,0.000500998,0.0007260833],"category_scores_gemma":[0.003071119,0.0003454236,0.0003921708,0.0002798935,0.0004846028,0.001084471,0.0008895713,0.0007333195,0.0005000536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002373036,"about_ca_system_score_gemma":0.0008462612,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008580581,"about_ca_topic_score_gemma":0.001455926,"domain_scores_codex":[0.9993819,0.0001541685,0.00002815071,0.00008747841,0.0002959215,0.00005236183],"domain_scores_gemma":[0.9987403,0.0005036904,0.0001810566,0.0002713343,0.0002652999,0.0000384046],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003981367,0.0001276242,0.002204139,0.0002268948,0.00009836369,0.000213487,0.0002696316,0.3608766,0.1671824,0.0205809,0.002504004,0.4453177],"study_design_scores_gemma":[0.00001158519,0.00007558637,0.0004719477,0.000008735842,0.00001068922,0.000178715,0.00001325973,0.9691694,0.02612277,0.002710937,0.001199974,0.0000264852],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007135856,0.00008306764,0.9920861,0.00002383792,0.00001508934,0.000007336466,0.0000170107,0.0002840868,0.0003475356],"genre_scores_gemma":[0.4904315,0.0003283985,0.5068572,0.00006649835,0.00006780784,0.00004375161,0.0001341381,0.00006493989,0.00200574],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0008580581,"threshold_uncertainty_score":0.002933085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01214208019179506,"score_gpt":0.2626215123910833,"score_spread":0.2504794321992883,"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."}}