{"id":"W2083930122","doi":"10.1109/vetecf.2011.6093164","title":"Multi-User MIMO Precoder Design via Genetic Search","year":2011,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Trois-Rivières","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Codebook; Precoding; MIMO; Computer science; Transmitter; Grassmannian; Algorithm; Computational complexity theory; Theoretical computer science; Computer engineering; Decoding methods; Mathematical optimization; Mathematics; Computer network; Telecommunications; Beamforming","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":[0.000340646,0.0004162218,0.0004793306,0.0003619887,0.0001856108,0.0004209611,0.0006519262,0.0006699018,0.0009504061],"category_scores_gemma":[0.000903241,0.0002407751,0.0003052898,0.0004025556,0.000328855,0.0003664154,0.0003056504,0.0004393208,0.0002954697],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004274162,"about_ca_system_score_gemma":0.0007398546,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001918379,"about_ca_topic_score_gemma":0.002647117,"domain_scores_codex":[0.9997596,0.00005912779,0.000008797585,0.0000439496,0.0001019043,0.0000265999],"domain_scores_gemma":[0.9997779,0.00009489114,0.00002494127,0.00001722715,0.00007506371,0.00001007889],"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":[0.00005594368,0.00005297551,0.0004714857,0.00008653248,0.00006795343,0.00009458814,0.00007728147,0.8237672,0.01645385,0.01620322,0.0008950997,0.1417738],"study_design_scores_gemma":[0.00002082328,0.00003924012,0.00008908224,0.000007263615,0.00001087854,0.0000438088,0.000007503598,0.9928154,0.003137699,0.00253476,0.001286348,0.000007156188],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007853651,0.0001362725,0.9902309,0.00005604442,0.0000205753,0.00002505616,0.00001235614,0.0001332342,0.001531982],"genre_scores_gemma":[0.3433709,0.000425762,0.6524617,0.0001279308,0.00004468827,0.0001932586,0.00007605733,0.00004548248,0.0032543],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.001918379,"threshold_uncertainty_score":0.003814399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04975525985631618,"score_gpt":0.2410899502375783,"score_spread":0.1913346903812621,"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."}}