{"id":"W3162269318","doi":"10.1109/wcnc49053.2021.9417277","title":"Swarm Intelligence based Power Allocation in Hybrid Millimeter-Wave Massive MIMO Systems","year":2021,"lang":"en","type":"article","venue":"","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"MIMO; Overhead (engineering); Channel state information; Radio frequency; Computer science; Spectral efficiency; Precoding; Telecommunications link; Transmitter power output; Base station; Particle swarm optimization; Electronic engineering; Channel (broadcasting); Transmitter; Real-time computing; Algorithm; Computer network; Engineering; Wireless; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000188267,0.0001765939,0.0001956377,0.0001677952,0.00002954055,0.0000724069,0.0001151178,0.00006563513,0.000302626],"category_scores_gemma":[0.00007451329,0.0001818609,0.00006328525,0.000249997,0.00001374025,0.0001217186,0.00003684842,0.0001594741,0.0001238863],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001250737,"about_ca_system_score_gemma":0.00004693236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004022421,"about_ca_topic_score_gemma":0.00003334563,"domain_scores_codex":[0.9988089,0.00005599029,0.0004131738,0.000270886,0.0001896686,0.000261415],"domain_scores_gemma":[0.9992775,0.00006760122,0.00003262392,0.0003878057,0.0001464825,0.00008803469],"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":[0.000007733662,0.0000620322,0.00007456759,0.0001671333,0.00004138101,0.0001105671,0.000292172,0.9143283,0.08049028,0.000295013,0.0006281756,0.003502626],"study_design_scores_gemma":[0.00009992813,0.00001137329,0.00001938372,0.00005757525,0.000005193826,0.000008999509,0.0002238087,0.5964568,0.4024844,0.0000848283,0.0003927505,0.0001549567],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1040563,0.0006437069,0.8885834,0.0001430403,0.0005603894,0.0001939467,0.000007514774,0.0001806062,0.005631039],"genre_scores_gemma":[0.9912693,0.00009213784,0.007978452,0.0001948389,0.0000327565,0.0000388593,0.00005128354,0.00003519504,0.0003071683],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.887213,"threshold_uncertainty_score":0.7416073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02872039834081419,"score_gpt":0.2264035012419091,"score_spread":0.1976831029010949,"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."}}