{"id":"W4372190821","doi":"10.1109/icassp49357.2023.10095418","title":"Downlink Covariance Estimation in URA FDD Massive MIMO Systems","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ericsson (Canada); Carleton University","funders":"","keywords":"Telecommunications link; Covariance matrix; Covariance; Computer science; MIMO; Transformation (genetics); Algorithm; Base station; Topology (electrical circuits); Antenna (radio); Control theory (sociology); Mathematics; Electronic engineering; Channel (broadcasting); Telecommunications; Engineering; Statistics","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":[0.0007848929,0.0006390586,0.0007209167,0.000246936,0.0002730359,0.0007235201,0.0005751468,0.000382604,0.0005143735],"category_scores_gemma":[0.002260207,0.0003871946,0.0003487843,0.0004913229,0.0004584496,0.0006271967,0.001078948,0.0006886467,0.0002988233],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003793155,"about_ca_system_score_gemma":0.0007285637,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00216344,"about_ca_topic_score_gemma":0.001871117,"domain_scores_codex":[0.9993429,0.0002258945,0.00002824954,0.00009869353,0.0002200105,0.00008423113],"domain_scores_gemma":[0.9992102,0.0003422361,0.0001330231,0.0001343983,0.0001508709,0.00002909187],"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":[0.0001361835,0.00003778644,0.001128061,0.0001165127,0.00005965229,0.0001696665,0.00007839844,0.8626479,0.01828815,0.02277641,0.001178029,0.09338334],"study_design_scores_gemma":[0.000005683169,0.00002256594,0.0001844028,0.00000422212,0.000006344744,0.00003340671,0.000006189794,0.9953231,0.002356356,0.001700745,0.0003484218,0.000008496605],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01458007,0.0001987581,0.9840134,0.00008738667,0.00002904995,0.00001190948,0.00004461041,0.0001701333,0.0008647454],"genre_scores_gemma":[0.7832607,0.0005285933,0.2139452,0.0001328446,0.0000927515,0.00006577775,0.0001557548,0.00003497743,0.001783388],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00216344,"threshold_uncertainty_score":0.004301727,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01081595447623739,"score_gpt":0.2325541395346418,"score_spread":0.2217381850584044,"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."}}