{"id":"W2161776610","doi":"10.1109/wcnc.2008.10","title":"Subspace Blind MIMO-OFDM Channel Estimation with Short Averaging Periods: Performance Analysis","year":2008,"lang":"en","type":"article","venue":"","topic":"Blind Source Separation Techniques","field":"Computer Science","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Algorithm; Orthogonal frequency-division multiplexing; Cyclic prefix; Subspace topology; Signal subspace; Computer science; Linear subspace; Channel (broadcasting); MIMO; Mathematics; Orthogonality; Noise (video); Telecommunications; 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":[0.001878416,0.0007868426,0.0008905772,0.0005679874,0.0004299271,0.0006607239,0.0003823129,0.0009429991,0.001020048],"category_scores_gemma":[0.008247065,0.0002414139,0.000339466,0.0008904371,0.0008120539,0.001384417,0.0009023039,0.000673042,0.0003603229],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004648143,"about_ca_system_score_gemma":0.0008002536,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001493875,"about_ca_topic_score_gemma":0.001186588,"domain_scores_codex":[0.9985842,0.0006331337,0.00005662542,0.0001052991,0.0004669344,0.0001539206],"domain_scores_gemma":[0.9939335,0.004439343,0.000397477,0.0004184097,0.0007176351,0.00009355947],"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":[0.000806745,0.0001078914,0.001715881,0.0002612156,0.00011708,0.0001327294,0.0001286507,0.8259132,0.01744988,0.02019041,0.0009182703,0.132258],"study_design_scores_gemma":[0.000007706639,0.00009047941,0.0003524882,0.00000645287,0.00001188602,0.00007358563,0.00001397175,0.9928479,0.004968805,0.001445963,0.0001678478,0.00001279843],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04586776,0.0009452785,0.9505812,0.0001359456,0.00003051914,0.00003260762,0.00004038667,0.0003888457,0.001977534],"genre_scores_gemma":[0.8394933,0.001061506,0.1580631,0.00006799868,0.00006968794,0.0001003478,0.0001210389,0.00004075171,0.0009822783],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001878416,"threshold_uncertainty_score":0.009934127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02467364348351301,"score_gpt":0.2521624664516644,"score_spread":0.2274888229681514,"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."}}