{"id":"W4315777458","doi":"10.1109/gcwkshps56602.2022.10008738","title":"Power Allocation for a HAPS-Enabled MIMO NOMA System with Spatially Correlated Channels","year":2022,"lang":"en","type":"article","venue":"2022 IEEE Globecom Workshops (GC Wkshps)","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; Channel (broadcasting); Computer network; Quality of service; Base station; MIMO; Interference (communication); Spatial correlation; Wireless; Noma; Real-time computing; Telecommunications; Telecommunications link","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"],"consensus_categories":[],"category_scores_codex":[0.0003264597,0.0003242595,0.0003351117,0.0001947782,0.0005333524,0.0001203336,0.0003773534,0.0001297239,0.0005825473],"category_scores_gemma":[0.00001183507,0.0003439272,0.0001055593,0.001030802,0.00002683047,0.0001913059,0.00006180754,0.0003266081,0.00004461744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005553518,"about_ca_system_score_gemma":0.00007328331,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005183203,"about_ca_topic_score_gemma":0.00006450788,"domain_scores_codex":[0.998184,0.00005941905,0.0004663283,0.0004568143,0.0003556534,0.0004777517],"domain_scores_gemma":[0.9989262,0.00009447561,0.0001472788,0.000551828,0.0001536363,0.0001265582],"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":[0.0001198119,0.00008861747,0.00009065078,0.00008346084,0.0001340265,0.000007126918,0.0004233822,0.9751913,0.0005614733,0.001643131,0.02063857,0.001018475],"study_design_scores_gemma":[0.001306525,0.0001635444,0.0001574592,0.00005342736,0.00007937023,0.0000421622,0.0008167733,0.9781694,0.0003201184,0.0000461116,0.0183494,0.0004957441],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07543768,0.0004812195,0.9101418,0.0004098253,0.002832833,0.002859868,0.0001989854,0.001431979,0.006205824],"genre_scores_gemma":[0.9915178,0.00001659626,0.003799872,0.0001022957,0.0001641482,0.00246896,0.000488403,0.0001345333,0.001307357],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9160802,"threshold_uncertainty_score":0.9999013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005573730909842963,"score_gpt":0.1873845728747569,"score_spread":0.181810841964914,"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."}}