{"id":"W2017532877","doi":"10.1002/ett.1429","title":"Covariance precoding schemes for MIMO OFDM over transmit‐antenna and path‐correlated channels","year":2010,"lang":"en","type":"article","venue":"European Transactions on Telecommunications","topic":"Advanced Wireless Communication Techniques","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Spinal Cord Injury Alberta; University of Alberta","funders":"","keywords":"Precoding; Orthogonal frequency-division multiplexing; Pairwise error probability; MIMO; MIMO-OFDM; Computer science; Covariance; Bit error rate; Algorithm; Control theory (sociology); Transmitter; Mathematics; Telecommunications; Statistics; Decoding methods; Beamforming; 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":[0.0006008596,0.0004568994,0.0004228282,0.0001712344,0.0003169505,0.0005734579,0.0005044121,0.0004054298,0.0008598648],"category_scores_gemma":[0.002636572,0.0002409376,0.0003092613,0.0004488569,0.0006491845,0.0005473637,0.0005158439,0.0005100484,0.0002378522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005322881,"about_ca_system_score_gemma":0.0009715187,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002159953,"about_ca_topic_score_gemma":0.00359092,"domain_scores_codex":[0.9993943,0.0002021727,0.00002360756,0.00006555724,0.0002366181,0.0000778271],"domain_scores_gemma":[0.9988837,0.0005787062,0.000156818,0.0001304059,0.0002253927,0.00002502222],"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":[0.0002275388,0.00009351879,0.001293319,0.0001308315,0.00009353537,0.0003348216,0.0002047537,0.7022294,0.03132119,0.08910481,0.001725559,0.1732408],"study_design_scores_gemma":[0.0000139318,0.00006151888,0.0003177895,0.000009966866,0.00001560485,0.00009431208,0.00001512654,0.9855435,0.005295734,0.007772523,0.0008484611,0.00001162616],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04981615,0.0004079562,0.9460524,0.0001791512,0.00004409734,0.00002861524,0.00004183685,0.0001102275,0.003319572],"genre_scores_gemma":[0.8878548,0.0005095261,0.1086455,0.00009428458,0.00007495117,0.00004971671,0.00006153826,0.00002014642,0.002689572],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002159953,"threshold_uncertainty_score":0.004294753,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01376464893858873,"score_gpt":0.2429961548389397,"score_spread":0.2292315059003509,"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."}}