{"id":"W2964218543","doi":"10.1109/jsac.2017.2698958","title":"Hybrid Analog and Digital Beamforming for mmWave OFDM Large-Scale Antenna Arrays","year":2017,"lang":"en","type":"article","venue":"IEEE Journal on Selected Areas in Communications","topic":"Millimeter-Wave Propagation and Modeling","field":"Engineering","cited_by":486,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Beamforming; Computer science; Baseband; MIMO; Electronic engineering; WSDMA; Transmitter; Spectral efficiency; Orthogonal frequency-division multiplexing; Precoding; Broadband; Multiplexing; Radio frequency; Antenna (radio); Telecommunications; Bandwidth (computing); Engineering; Channel (broadcasting)","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002585223,0.0007180767,0.0003711265,0.0003029688,0.0003140212,0.0005452468,0.0005148891,0.0005257564,0.00261497],"category_scores_gemma":[0.0007337498,0.0002735716,0.0003348154,0.0005723136,0.0003783198,0.0006736575,0.0005600797,0.0004628116,0.0009052585],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003330193,"about_ca_system_score_gemma":0.0003322145,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006410537,"about_ca_topic_score_gemma":0.001836529,"domain_scores_codex":[0.9997715,0.00007469703,0.000010281,0.00003536068,0.00008595387,0.00002222756],"domain_scores_gemma":[0.9997348,0.0001238401,0.0000361186,0.00003224966,0.00005562716,0.00001726105],"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":[0.0001114727,0.00004340352,0.0004987344,0.0001138627,0.00004270055,0.000077636,0.00007502332,0.6480938,0.03499814,0.03065197,0.002226637,0.2830667],"study_design_scores_gemma":[0.00001048179,0.00005451051,0.00008524386,0.000006544552,0.00000609661,0.00003428122,0.00001402683,0.989433,0.003624675,0.005029503,0.001692834,0.000008804289],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.002963037,0.00009527319,0.9952574,0.0000384412,0.00001127126,0.00001272999,0.00001137998,0.00009699036,0.001513345],"genre_scores_gemma":[0.3198726,0.0004035246,0.6752551,0.0001413672,0.00006170035,0.0001442559,0.0001076191,0.000036107,0.00397772],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00261497,"threshold_uncertainty_score":0.008747935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03551198410412842,"score_gpt":0.2804411348638237,"score_spread":0.2449291507596953,"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."}}