{"id":"W2130462143","doi":"10.1109/tvt.2011.2153218","title":"Semiblind Sparse Channel Estimation for MIMO-OFDM Systems","year":2011,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Orthogonal frequency-division multiplexing; MIMO; MIMO-OFDM; Algorithm; Channel (broadcasting); Sparse approximation; Computer science; Impulse (physics); Mathematics; 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":[0.0007255161,0.0006219489,0.0007156125,0.0004296452,0.0004766222,0.0007387674,0.0005455628,0.0006796443,0.001381796],"category_scores_gemma":[0.003633288,0.0002995892,0.000390697,0.0003766576,0.0007012536,0.001092997,0.0009254956,0.0009162526,0.0005679573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004000837,"about_ca_system_score_gemma":0.0009350575,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008359295,"about_ca_topic_score_gemma":0.001216285,"domain_scores_codex":[0.999173,0.0002868632,0.00003257057,0.0001123816,0.0003349369,0.00006028378],"domain_scores_gemma":[0.9982899,0.0009405655,0.0002235205,0.0001916567,0.0003104734,0.00004385077],"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":[0.000501564,0.0001341846,0.00103355,0.0002779311,0.00009415743,0.0001569258,0.0002194213,0.5853734,0.06160296,0.03304688,0.002293288,0.3152658],"study_design_scores_gemma":[0.00001502295,0.00006681819,0.0001946896,0.000008562096,0.000007943392,0.0000794742,0.00001557489,0.9834696,0.008744957,0.006263985,0.001114985,0.00001845468],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003840975,0.00006397159,0.9955634,0.00003674339,0.00001302432,0.00001139392,0.00001580953,0.0001381446,0.0003165106],"genre_scores_gemma":[0.354874,0.0003789116,0.6421131,0.000111526,0.0001034149,0.00009943941,0.0001660202,0.00007675506,0.002076721],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001381796,"threshold_uncertainty_score":0.004622519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03061368393779725,"score_gpt":0.2456346503191979,"score_spread":0.2150209663814006,"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."}}