{"id":"W2940781481","doi":"10.1186/s13638-019-1366-8","title":"Diversity gain of millimeter-wave massive MIMO systems with distributed antenna arrays","year":2019,"lang":"en","type":"article","venue":"EURASIP Journal on Wireless Communications and Networking","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Fundamental Research Funds for the Central Universities; Natural Science Foundation of Liaoning Province","keywords":"Diversity gain; Computer science; Antenna (radio); MIMO; Transmitter; Distributed antenna system; Diversity scheme; Antenna diversity; Extremely high frequency; Antenna gain; Array gain; Electronic engineering; Telecommunications; Antenna array; Antenna aperture; Radiation pattern; Fading; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002358759,0.0001641556,0.0003047909,0.0001083835,0.0005007873,0.00004861493,0.0003028263,0.00006322932,0.000002943233],"category_scores_gemma":[0.000003991417,0.0001424907,0.00004493865,0.0002684563,0.00006548134,0.0001855768,0.0002087418,0.0003722527,0.000002012945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008834465,"about_ca_system_score_gemma":0.00001100078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008390186,"about_ca_topic_score_gemma":0.000007437173,"domain_scores_codex":[0.9990489,0.0001349876,0.0003474245,0.0001153499,0.000149217,0.0002041595],"domain_scores_gemma":[0.9987033,0.0002235646,0.0002778316,0.0005684074,0.0001412139,0.00008569897],"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":[0.00008332117,0.00007579938,0.03258347,0.0001541441,0.0003262706,0.00001746595,0.001532726,0.9567794,0.002648642,0.0006296799,0.00008038314,0.005088698],"study_design_scores_gemma":[0.0007586275,0.0001678107,0.001011354,0.001369945,0.0000454928,0.0001235905,0.00079235,0.9945221,0.0001158966,0.00003031888,0.0007973669,0.0002651635],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4108663,0.005618918,0.5815895,0.00007941564,0.000518323,0.0004064118,0.00003085871,0.00009764454,0.0007926481],"genre_scores_gemma":[0.9934441,0.004497086,0.001900788,0.000008890044,0.0000707735,0.000004757605,0.00002562537,0.00002987822,0.00001811741],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5825778,"threshold_uncertainty_score":0.5810601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02430295844002112,"score_gpt":0.2186330204804088,"score_spread":0.1943300620403877,"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."}}