{"id":"W3200564414","doi":"10.1109/apwc52648.2021.9539866","title":"Massive-Beam MIMO for LEO/VLEO VHTS","year":2021,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Huawei Technologies (Canada)","funders":"","keywords":"MIMO; Precoding; Computer science; Electronic engineering; Coherence (philosophical gambling strategy); Array gain; Channel (broadcasting); Phased array; 3G MIMO; Beam (structure); Transmission (telecommunications); Array processing; Channel state information; Communications satellite; Telecommunications; Satellite; Wireless; Antenna array; Signal processing; Antenna (radio); Physics; Engineering; Optics; Aerospace engineering","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":[0.0001933811,0.0003231163,0.0002484967,0.000122789,0.000179714,0.0003420206,0.0002688392,0.0002351275,0.001306521],"category_scores_gemma":[0.000285629,0.0001126174,0.000226867,0.0002136784,0.0002480501,0.0003134099,0.0005062037,0.0004306782,0.000353547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002229742,"about_ca_system_score_gemma":0.0002910516,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007039094,"about_ca_topic_score_gemma":0.0009736482,"domain_scores_codex":[0.9998509,0.00003807621,0.000003528518,0.00002154766,0.00006373895,0.00002217564],"domain_scores_gemma":[0.9998963,0.00003231707,0.00001610818,0.0000164315,0.0000258523,0.00001299995],"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":[0.0002270202,0.0000837038,0.001459815,0.0002203299,0.00007145208,0.0004329202,0.00015729,0.514011,0.1459049,0.1060384,0.007738695,0.2236545],"study_design_scores_gemma":[0.00002417068,0.0001607254,0.0007091277,0.00001802713,0.00001157019,0.000189788,0.00004073685,0.9592505,0.01336113,0.01728637,0.008924345,0.00002342812],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01937166,0.0005181704,0.9698224,0.0002412124,0.0001180633,0.00002484835,0.00007915882,0.0002451977,0.009579267],"genre_scores_gemma":[0.7444974,0.0008270536,0.248364,0.000243936,0.000175964,0.00008817429,0.0001500003,0.00002568417,0.005627878],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001306521,"threshold_uncertainty_score":0.004370809,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01121509010019058,"score_gpt":0.228381650647922,"score_spread":0.2171665605477314,"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."}}