{"id":"W4385688967","doi":"10.1109/bsc57238.2023.10201832","title":"Compressive Sensing-Based Channel Estimation for MIMO OTFS Systems","year":2023,"lang":"en","type":"article","venue":"","topic":"PAPR reduction in OFDM","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Matching pursuit; Compressed sensing; Algorithm; MIMO; Channel (broadcasting); Block (permutation group theory); Computer science; Orthogonal frequency-division multiplexing; MIMO-OFDM; Modulation (music); Minimum mean square error; Frequency domain; Mathematics; Telecommunications; Computer vision; Statistics; Acoustics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000269388,0.0003887415,0.0003264628,0.000231026,0.0001990447,0.0002863355,0.000321934,0.0003722847,0.0006666381],"category_scores_gemma":[0.001545225,0.0001371934,0.0001676395,0.0003534794,0.0003655102,0.0006360376,0.0004033343,0.0004926569,0.000156198],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002211056,"about_ca_system_score_gemma":0.000483764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001739001,"about_ca_topic_score_gemma":0.002294283,"domain_scores_codex":[0.9997255,0.00006790476,0.0000114839,0.00003688838,0.0001349172,0.00002327162],"domain_scores_gemma":[0.9995598,0.0002424199,0.00006207792,0.00004554322,0.0000768779,0.00001329122],"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":[0.000250923,0.00006952944,0.0009322781,0.0001745283,0.00004558399,0.0001406091,0.0001138039,0.6192883,0.06267376,0.02218349,0.002042904,0.2920842],"study_design_scores_gemma":[0.000007791684,0.00002807612,0.0001967153,0.000007278964,0.000003619905,0.00004653996,0.00001281884,0.991457,0.005625533,0.001915926,0.0006906767,0.000008009067],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01463455,0.0002249121,0.9836589,0.0001557699,0.00003570817,0.0000205071,0.00003330454,0.0001280303,0.001108339],"genre_scores_gemma":[0.6992998,0.0007927855,0.2976092,0.0001320354,0.0001398704,0.00008733038,0.0001525655,0.00002369619,0.00176273],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001739001,"threshold_uncertainty_score":0.003457785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02564855059319891,"score_gpt":0.2549543104324394,"score_spread":0.2293057598392405,"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."}}