{"id":"W2108910393","doi":"10.1109/rws.2006.1615097","title":"Mimo capacity improvement using smart passive receive antennas","year":2006,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"MIMO; Weighting; Antenna (radio); Computer science; Smart antenna; Electronic engineering; 3G MIMO; Channel capacity; Reconfigurable antenna; Radio frequency; Limit (mathematics); Process (computing); Telecommunications; Directional antenna; Engineering; Mathematics; Antenna efficiency; Omnidirectional antenna; Acoustics; Physics; Beamforming; 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":[0.0002220798,0.0006112448,0.0004384955,0.000229691,0.0001890085,0.0003554668,0.0004601045,0.0004536125,0.001603716],"category_scores_gemma":[0.000844788,0.0002155804,0.0002972752,0.0002386138,0.0004407735,0.0008169833,0.0006028506,0.000403521,0.0007888543],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002119231,"about_ca_system_score_gemma":0.0001503483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001182942,"about_ca_topic_score_gemma":0.0002589594,"domain_scores_codex":[0.999779,0.00006170071,0.000009096464,0.00003927359,0.00007521758,0.00003571739],"domain_scores_gemma":[0.999345,0.0003049884,0.0000778102,0.00009565306,0.0001453758,0.00003119042],"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":[0.0005580311,0.0001443181,0.001292887,0.0002535523,0.0001123652,0.00041411,0.0001564456,0.1805623,0.5879847,0.04753886,0.002926453,0.178056],"study_design_scores_gemma":[0.00005894915,0.0007598574,0.001107754,0.00002573029,0.0001023696,0.0008377066,0.00004685099,0.7558972,0.2182623,0.01270564,0.01013825,0.00005746866],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.104402,0.0004932969,0.8819785,0.0002123093,0.00009591988,0.00002267956,0.00005826758,0.0009073899,0.01182974],"genre_scores_gemma":[0.8743401,0.000363688,0.1214155,0.0001860013,0.0001400309,0.00002989045,0.00009617657,0.00006392624,0.003364876],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001603716,"threshold_uncertainty_score":0.005365014,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01221807090634944,"score_gpt":0.2080782411371932,"score_spread":0.1958601702308438,"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."}}