{"id":"W2750780858","doi":"10.3390/electronics6030063","title":"Massive MIMO Wireless Networks: An Overview","year":2017,"lang":"en","type":"article","venue":"Electronics","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Ontario Centres of Excellence","keywords":"MIMO; Beamforming; Precoding; Computer science; Multi-user MIMO; 3G MIMO; Electronic engineering; Wireless; Overhead (engineering); Broadband; Key (lock); Computer engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007937637,0.0001374713,0.0001567057,0.0000233113,0.0001924268,0.00009311736,0.0002948483,0.00008912908,0.00001845375],"category_scores_gemma":[0.00001391094,0.00014963,0.00003320619,0.0000446199,0.0000196305,0.000445161,0.00002607107,0.0001794923,0.00002286396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000152253,"about_ca_system_score_gemma":0.00002233849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000344796,"about_ca_topic_score_gemma":0.0001376303,"domain_scores_codex":[0.9992551,0.0000157739,0.0001418953,0.0001542757,0.00007122356,0.0003617222],"domain_scores_gemma":[0.9991979,0.00001124449,0.00007073685,0.0006186055,0.00003667427,0.00006486762],"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":[0.000004286167,0.00001144291,0.0001334717,0.00004109584,0.00003282767,0.00000530814,0.00006270859,0.9573748,0.0007187266,0.008020215,0.000561598,0.0330335],"study_design_scores_gemma":[0.0002917379,0.00005360167,0.0002015072,0.00005091587,0.00001566331,0.000006434918,0.00001430197,0.9747722,0.001400564,0.0006650629,0.02223972,0.0002882669],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0284091,0.07628118,0.8854818,0.0001073987,0.001345258,0.0005588189,0.00000756459,0.001027549,0.006781324],"genre_scores_gemma":[0.9873828,0.01023485,0.001637836,0.00002879465,0.0003110952,0.00003023449,0.00002527267,0.00007821224,0.0002708661],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9589738,"threshold_uncertainty_score":0.6101733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01564473410684731,"score_gpt":0.2615307331172148,"score_spread":0.2458859990103675,"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."}}