{"id":"W2788350651","doi":"10.1109/tsp.2018.2812733","title":"Fractional Programming for Communication Systems—Part I: Power Control and Beamforming","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Signal Processing","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":1808,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Beamforming; Mathematical optimization; Optimization problem; Quadratic programming; Convex optimization; Maximization; Computer science; Iterative method; Mathematics; Convergence (economics); Fractional programming; Regular polygon; Nonlinear programming","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":[0.001074034,0.00109541,0.0007242786,0.000462483,0.0004904243,0.001636288,0.0006440526,0.001298627,0.004075126],"category_scores_gemma":[0.002093645,0.0003116861,0.0005885047,0.00117009,0.001449314,0.001493602,0.0009730009,0.002001497,0.0007066157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009932739,"about_ca_system_score_gemma":0.0007918473,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00102259,"about_ca_topic_score_gemma":0.0006254021,"domain_scores_codex":[0.9993994,0.0002672728,0.00002982754,0.00008343949,0.0001724455,0.00004768119],"domain_scores_gemma":[0.9994223,0.0004101857,0.00005469888,0.00004368384,0.00005728459,0.00001187914],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00002839558,0.00004121895,0.0001405669,0.0003787168,0.00003264032,0.00008775463,0.0001095385,0.218922,0.003259574,0.634674,0.008345337,0.1339801],"study_design_scores_gemma":[0.00001195654,0.00009726036,0.0001842297,0.000130345,0.0000190094,0.0001167047,0.00004708459,0.6354703,0.001661198,0.3194752,0.04276302,0.000023684],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001285653,0.004767038,0.9761842,0.0009391694,0.0003063463,0.00002940976,0.00003750748,0.00006541407,0.01638526],"genre_scores_gemma":[0.4154255,0.02929468,0.5169806,0.001622071,0.002916462,0.0005973494,0.0001639738,0.0002366846,0.03276258],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004075126,"threshold_uncertainty_score":0.01363271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01293441291470982,"score_gpt":0.2486897928834811,"score_spread":0.2357553799687713,"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."}}