{"id":"W4385627168","doi":"10.1109/twc.2023.3300719","title":"Reconfigurable Intelligent Surface-Aided Full-Duplex mmWave MIMO: Channel Estimation, Passive and Hybrid Beamforming","year":2023,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Full-Duplex Wireless Communications","field":"Engineering","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"National Key Research and Development Program of China; Natural Science Foundation of Sichuan Province","keywords":"Beamforming; Computer science; MIMO; Telecommunications link; Spectral efficiency; Channel (broadcasting); Electronic engineering; Interference (communication); Minimum mean square error; Precoding; Planar array; Telecommunications; Estimator; Engineering; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts"],"consensus_categories":[],"category_scores_codex":[0.0003389569,0.0004864646,0.0004771846,0.0005429441,0.001386487,0.0001777357,0.001372505,0.0001906163,0.0000783447],"category_scores_gemma":[0.00002894483,0.0005731644,0.0001820442,0.001319546,0.0003750563,0.0005441266,0.0000284427,0.0009790891,0.0004636592],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002838238,"about_ca_system_score_gemma":0.00008238756,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001778749,"about_ca_topic_score_gemma":0.0005306057,"domain_scores_codex":[0.9975803,0.0001915699,0.0008515732,0.000428522,0.0003194202,0.0006285385],"domain_scores_gemma":[0.9951544,0.00102834,0.0001492223,0.003156354,0.0002386495,0.000273009],"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":[0.00001301406,0.0001419764,0.000002607933,0.0000679317,0.0001679329,0.000001788153,0.002196336,0.9602609,0.006127751,0.0003964918,0.0005020346,0.03012126],"study_design_scores_gemma":[0.0004188957,0.00005643371,0.00004542998,0.0002149317,0.00009412975,0.000030454,0.001894337,0.9624772,0.03298838,0.00008360577,0.001135667,0.0005605139],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6107057,0.000529414,0.3810304,0.002319279,0.0005825117,0.001024115,0.0005336333,0.002601297,0.0006736012],"genre_scores_gemma":[0.9827833,0.009930809,0.005783712,0.00007342437,0.00002100656,0.0004933797,0.0003514034,0.0001538662,0.0004091081],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3752467,"threshold_uncertainty_score":0.9999136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03224431997777141,"score_gpt":0.256474670109974,"score_spread":0.2242303501322026,"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."}}