{"id":"W3126714176","doi":"10.1109/tvt.2021.3057547","title":"Interference Cancellation Aided Hybrid Beamforming for mmWave Multi-User Massive MIMO Systems","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"Foundation for Innovative Research Groups of the National Natural Science Foundation of China; Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada","keywords":"Beamforming; Single antenna interference cancellation; MIMO; Computer science; Interference (communication); Electronic engineering; Spectral efficiency; Telecommunications link; Multi-user MIMO; WSDMA; Channel (broadcasting); Precoding; Telecommunications; Engineering","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":[0.000486369,0.0008381152,0.0005432444,0.0003947632,0.0003341906,0.0006143736,0.0005329969,0.0005695508,0.001685417],"category_scores_gemma":[0.0009007745,0.0002641847,0.0004616063,0.000642819,0.0003890601,0.0006254048,0.0006796871,0.0005452681,0.0007409443],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002507566,"about_ca_system_score_gemma":0.0004196061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007149765,"about_ca_topic_score_gemma":0.001362603,"domain_scores_codex":[0.999561,0.0001423505,0.00001743334,0.00004938784,0.000178973,0.00005090497],"domain_scores_gemma":[0.999576,0.0001879408,0.00005087215,0.0000433762,0.0001231832,0.00001854787],"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":[0.0002679476,0.00008209933,0.001152673,0.0002475276,0.0001532316,0.0001818752,0.0001427443,0.595875,0.069111,0.03668167,0.002589412,0.2935148],"study_design_scores_gemma":[0.00001609273,0.0001358366,0.000286036,0.00001261902,0.00001920484,0.00009726894,0.00001765225,0.9831948,0.009016735,0.004990675,0.002191207,0.00002201328],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005148594,0.0002622242,0.992792,0.00005175594,0.00002579037,0.00001487641,0.00002399813,0.0001502376,0.001530494],"genre_scores_gemma":[0.5206991,0.0009749332,0.4716637,0.0003752245,0.0001577643,0.0001709441,0.0002162367,0.0000478132,0.005694306],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001685417,"threshold_uncertainty_score":0.005638242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02169625104950047,"score_gpt":0.2347901435804441,"score_spread":0.2130938925309436,"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."}}