{"id":"W4387350722","doi":"10.1109/access.2023.3321681","title":"Hybrid Precoding/Combining for mmWave MIMO Systems With Hybrid Array Architecture","year":2023,"lang":"en","type":"article","venue":"IEEE Access","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada; University of Ottawa","funders":"","keywords":"Precoding; MIMO; Computer science; Spectral efficiency; Transmitter; Electronic engineering; Block (permutation group theory); Spatial multiplexing; Radio frequency; Cellular architecture; Algorithm; Computer network; Mathematics; Telecommunications; Engineering; Channel (broadcasting)","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":[0.0001401166,0.0004486548,0.0001843606,0.0002091537,0.0002087748,0.0005558372,0.0003780933,0.0003330618,0.002958946],"category_scores_gemma":[0.0001801255,0.0001318563,0.0002479919,0.0003609978,0.0001891834,0.0004433372,0.0002435761,0.0002239314,0.0009675734],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002459161,"about_ca_system_score_gemma":0.0001827541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005871939,"about_ca_topic_score_gemma":0.001390749,"domain_scores_codex":[0.9998122,0.0000502255,0.000009489299,0.00003007806,0.00007709388,0.00002089139],"domain_scores_gemma":[0.9998657,0.00003040102,0.00002506541,0.00002397925,0.00004833494,0.000006544542],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002821349,0.00009382758,0.001863367,0.0002095011,0.0002084972,0.0002504213,0.0001562622,0.1427357,0.4220652,0.02386935,0.004126776,0.404139],"study_design_scores_gemma":[0.000027258,0.000618932,0.001453845,0.00002601833,0.00006524702,0.0005109899,0.00006390002,0.8524414,0.1217781,0.004581823,0.01839087,0.00004166139],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.04955376,0.0004360951,0.9377989,0.0001150831,0.00006417507,0.00004686537,0.00007713518,0.0006167799,0.01129117],"genre_scores_gemma":[0.641054,0.0003697964,0.350971,0.0001519466,0.00009366321,0.00009573233,0.0001608563,0.00003801122,0.007065096],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002958946,"threshold_uncertainty_score":0.009898663,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04062925064301054,"score_gpt":0.2653108734271828,"score_spread":0.2246816227841723,"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."}}