{"id":"W1662081346","doi":"10.1109/tsp.2015.2460223","title":"Linear Beamformer Design for Interference Alignment via Rank Minimization","year":2015,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Matrix norm; Telecommunications link; Interference alignment; Algorithm; Minification; Rank (graph theory); Low-rank approximation; Interference (communication); Matrix (chemical analysis); Computer science; Mathematics; Norm (philosophy); Mathematical optimization; Beamforming; Telecommunications; MIMO; Combinatorics","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":[0.001290641,0.001557232,0.001048926,0.0004569183,0.0003492369,0.0009448567,0.001227528,0.0009905612,0.003503429],"category_scores_gemma":[0.003327757,0.0006077121,0.0007738921,0.0007167384,0.000951368,0.001382182,0.001154049,0.001473223,0.001996212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004969451,"about_ca_system_score_gemma":0.001080878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009824487,"about_ca_topic_score_gemma":0.001324915,"domain_scores_codex":[0.9985828,0.0006056141,0.00005590179,0.0002465927,0.0004082079,0.0001008817],"domain_scores_gemma":[0.9989779,0.0004206018,0.0001593133,0.0001304009,0.0002748288,0.00003693127],"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":[0.0001271342,0.00007030417,0.000367127,0.0001774041,0.00008736146,0.00007951962,0.0001849601,0.7317921,0.01743492,0.06618771,0.003553778,0.1799377],"study_design_scores_gemma":[0.0000211807,0.00009880995,0.00008355748,0.00001534367,0.00001478675,0.00006299056,0.0000238124,0.9805056,0.003810555,0.01174637,0.00359948,0.0000175458],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0005165347,0.00002909549,0.9988838,0.00002026139,0.000006790814,0.00000755926,0.000007399286,0.0000557424,0.0004728787],"genre_scores_gemma":[0.1100607,0.0003388272,0.8849643,0.0001991378,0.00009809711,0.0002601734,0.0001732676,0.0001569162,0.003748627],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003503429,"threshold_uncertainty_score":0.01172018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04220756138108751,"score_gpt":0.2662238182560557,"score_spread":0.2240162568749682,"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."}}